diff --git a/example/concurrent-inferences.f90 b/example/concurrent-inferences.f90
new file mode 100644
index 000000000..42bf1213e
--- /dev/null
+++ b/example/concurrent-inferences.f90
@@ -0,0 +1,62 @@
+! Copyright (c), The Regents of the University of California
+! Terms of use are as specified in LICENSE.txt
+program concurrent_inference
+  !! This program demonstrates how to read a neural network from a JSON file
+  !! and use the network to perform concurrent inferences.
+  use inference_engine_m, only : inference_engine_t, tensor_t
+  use sourcery_m, only : string_t, command_line_t, file_t
+  use assert_m, only : assert
+  use iso_fortran_env, only : int64, real64
+  implicit none
+
+  type(string_t) network_file_name
+  type(command_line_t) command_line
+
+  network_file_name = string_t(command_line%flag_value("--network"))
+
+  if (len(network_file_name%string())==0) then
+    error stop new_line('a') // new_line('a') // &
+      'Usage: ./build/run-fpm.sh run --example identity -- --network "<file-name>"' 
+  end if
+
+  block 
+    type(inference_engine_t) network, inference_engine
+    type(tensor_t), allocatable :: inputs(:,:,:), outputs(:,:,:) 
+    real, allocatable :: input_components(:,:,:,:)
+    integer, parameter :: lat=263, lon=317, lev=15 ! latitudes, longitudes, levels (elevations)
+    integer i, j, k
+
+    print *, "Constructing a new inference_engine_t object from the file " // network_file_name%string()
+    inference_engine = inference_engine_t(file_t(network_file_name))
+
+    print *,"Defining an array of tensor_t input objects with random normalized components"
+    allocate(inputs(lat,lon,lev))
+    allocate(input_components(lat,lon,lev,inference_engine%num_inputs()))
+    call random_number(input_components)
+
+    do concurrent(i=1:lat, j=1:lon, k=1:lev)
+      inputs(i,j,k) = tensor_t(input_components(i,j,k,:))
+    end do
+
+    block 
+      integer(int64) t_start, t_finish, clock_rate
+
+      print *,"Performing elemental inferences"
+      call system_clock(t_start, clock_rate)
+      outputs = inference_engine%infer(inputs)  ! implicit allocation of outputs array
+      call system_clock(t_finish)
+      print *,"Elemental inference time: ", real(t_finish - t_start, real64)/real(clock_rate, real64)
+
+      call assert(all(shape(outputs) == shape(inputs)), "all(shape(outputs) == shape(inputs))")
+
+      print *,"Performing concurrent inference"
+      call system_clock(t_start)
+      do concurrent(i=1:lat, j=1:lon, k=1:lev)
+        outputs(i,j,k) = inference_engine%infer(inputs(i,j,k))           
+      end do
+      call system_clock(t_finish)
+      print *,"Concurrent inference time: ", real(t_finish - t_start, real64)/real(clock_rate, real64)
+    end block
+  end block
+
+end program