diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 4af28a993..95dba9133 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -35,7 +35,7 @@ jobs:
         python -m pip install --upgrade .[test]
     - name: Run unit tests
       run: |
-        pytest
+        python -m pytest
 
   test-coverage:
     name: Calculate and upload test coverage
diff --git a/setup.cfg b/setup.cfg
index 6660e83eb..067a87fc8 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -32,11 +32,11 @@ project_urls =
 packages = find:
 install_requires =
     colorlog
-    dspeed>=1.1
+    dspeed@git+https://github.com/legend-exp/dspeed@main
     h5py>=3.2
     iminuit
-    legend-daq2lh5>=1.1.0
-    legend-pydataobj>=1.3
+    legend-daq2lh5@git+https://github.com/legend-exp/legend-daq2lh5@main
+    legend-pydataobj>=1.5.0a1
     matplotlib
     numba!=0.53.*,!=0.54.*,!=0.57
     numpy>=1.21
diff --git a/src/pygama/cli.py b/src/pygama/cli.py
index a6b59abaf..fb05ef658 100644
--- a/src/pygama/cli.py
+++ b/src/pygama/cli.py
@@ -80,7 +80,7 @@ def pygama_cli():
 
 
 def add_lh5ls_parser(subparsers):
-    """Configure :func:`.lgdo.lh5_store.show` command line interface."""
+    """Configure :func:`.lgdo.lh5.show` command line interface."""
 
     parser_lh5ls = subparsers.add_parser(
         "lh5ls", description="""Inspect LEGEND HDF5 (LH5) file contents"""
@@ -99,7 +99,7 @@ def add_lh5ls_parser(subparsers):
 
 
 def lh5_show_cli(args):
-    """Passes command line arguments to :func:`.lgdo.lh5_store.show`."""
+    """Passes command line arguments to :func:`.lgdo.lh5.show`."""
 
     show(args.lh5_file, args.lh5_group, attrs=args.attributes)
 
diff --git a/src/pygama/evt/build_tcm.py b/src/pygama/evt/build_tcm.py
index 7bb0bbef3..e821ee50f 100644
--- a/src/pygama/evt/build_tcm.py
+++ b/src/pygama/evt/build_tcm.py
@@ -49,7 +49,7 @@ def build_tcm(
     out_name
         name for the TCM table in the output file.
     wo_mode
-        mode to send to :meth:`~.lgdo.lh5_store.LH5Store.write_object`.
+        mode to send to :meth:`~.lgdo.lh5.LH5Store.write`.
 
     See Also
     --------
@@ -79,7 +79,7 @@ def build_tcm(
                 else:
                     array_id = len(all_tables) - 1
                 table = table + "/" + coin_col
-                coin_data.append(store.read_object(table, filename)[0].nda)
+                coin_data.append(store.read(table, filename)[0].nda)
                 array_ids.append(array_id)
 
     tcm_cols = ptcm.generate_tcm_cols(
@@ -94,6 +94,6 @@ def build_tcm(
     )
 
     if out_file is not None:
-        store.write_object(tcm, out_name, out_file, wo_mode=wo_mode)
+        store.write(tcm, out_name, out_file, wo_mode=wo_mode)
 
     return tcm
diff --git a/src/pygama/flow/data_loader.py b/src/pygama/flow/data_loader.py
index 625b52fbc..a171ddfd3 100644
--- a/src/pygama/flow/data_loader.py
+++ b/src/pygama/flow/data_loader.py
@@ -14,7 +14,9 @@
 import numpy as np
 import pandas as pd
 from dspeed.vis import WaveformBrowser
-from lgdo import Array, LH5Iterator, LH5Store, Struct, Table, lgdo_utils
+from lgdo.lh5 import LH5Iterator, LH5Store
+from lgdo.lh5.utils import expand_vars
+from lgdo.types import Array, Struct, Table
 from lgdo.types.vectorofvectors import build_cl, explode_arrays, explode_cl
 from tqdm.auto import tqdm
 
@@ -193,9 +195,7 @@ def set_config(self, config: dict | str) -> None:
         # look for info in configuration if FileDB is not set
         if self.filedb is None:
             # expand $_ variables
-            value = lgdo_utils.expand_vars(
-                config["filedb"], substitute={"_": config_dir}
-            )
+            value = expand_vars(config["filedb"], substitute={"_": config_dir})
             self.filedb = FileDB(value)
 
         if not os.path.isdir(self.filedb.data_dir):
@@ -584,7 +584,7 @@ def build_entry_list(
 
             tcm_table_name = self.filedb.get_table_name(tcm_tier, tcm_tb)
             try:
-                tcm_lgdo, _ = sto.read_object(tcm_table_name, tcm_path)
+                tcm_lgdo, _ = sto.read(tcm_table_name, tcm_path)
             except KeyError:
                 log.warning(f"Cannot find table {tcm_table_name} in file {tcm_path}")
                 continue
@@ -649,7 +649,7 @@ def build_entry_list(
                             if tb in col_tiers[file]["tables"][tier]:
                                 table_name = self.filedb.get_table_name(tier, tb)
                                 try:
-                                    tier_table, _ = sto.read_object(
+                                    tier_table, _ = sto.read(
                                         table_name,
                                         tier_path,
                                         field_mask=cut_cols[level],
@@ -708,11 +708,9 @@ def build_entry_list(
                 f_dict = f_entries.to_dict("list")
                 f_struct = Struct(f_dict)
                 if self.merge_files:
-                    sto.write_object(f_struct, "entries", output_file, wo_mode="a")
+                    sto.write(f_struct, "entries", output_file, wo_mode="a")
                 else:
-                    sto.write_object(
-                        f_struct, f"entries/{file}", output_file, wo_mode="a"
-                    )
+                    sto.write(f_struct, f"entries/{file}", output_file, wo_mode="a")
 
         if log.getEffectiveLevel() >= logging.INFO:
             progress_bar.close()
@@ -862,7 +860,7 @@ def build_hit_entries(
                             # load the data from the tier file, just the columns needed for the cut
                             table_name = self.filedb.get_table_name(tier, tb)
                             try:
-                                tier_tb, _ = sto.read_object(
+                                tier_tb, _ = sto.read(
                                     table_name, tier_path, field_mask=cut_cols
                                 )
                             except KeyError:
@@ -902,11 +900,9 @@ def build_hit_entries(
                 f_dict = f_entries.to_dict("list")
                 f_struct = Struct(f_dict)
                 if self.merge_files:
-                    sto.write_object(f_struct, "entries", output_file, wo_mode="a")
+                    sto.write(f_struct, "entries", output_file, wo_mode="a")
                 else:
-                    sto.write_object(
-                        f_struct, f"entries/{file}", output_file, wo_mode="a"
-                    )
+                    sto.write(f_struct, f"entries/{file}", output_file, wo_mode="a")
 
         if log.getEffectiveLevel() >= logging.INFO:
             progress_bar.close()
@@ -1117,7 +1113,7 @@ def explode_evt_cols(el: pd.DataFrame, tier_table: Table):
                         for file in files
                     ]
 
-                    tier_table, _ = sto.read_object(
+                    tier_table, _ = sto.read(
                         name=tb_name,
                         lh5_file=tier_paths,
                         idx=idx_mask,
@@ -1143,7 +1139,7 @@ def explode_evt_cols(el: pd.DataFrame, tier_table: Table):
             f_table = utils.dict_to_table(col_dict=col_dict, attr_dict=attr_dict)
 
             if output_file:
-                sto.write_object(f_table, "merged_data", output_file, wo_mode="o")
+                sto.write(f_table, "merged_data", output_file, wo_mode="o")
             if in_memory:
                 if self.output_format == "lgdo.Table":
                     return f_table
@@ -1220,7 +1216,7 @@ def explode_evt_cols(el: pd.DataFrame, tier_table: Table):
                             raise FileNotFoundError(tier_path)
 
                         table_name = self.filedb.get_table_name(tier, tb)
-                        tier_table, _ = sto.read_object(
+                        tier_table, _ = sto.read(
                             table_name,
                             tier_path,
                             idx=idx_mask,
@@ -1246,7 +1242,7 @@ def explode_evt_cols(el: pd.DataFrame, tier_table: Table):
                 if in_memory:
                     load_out.add_field(name=file, obj=f_table)
                 if output_file:
-                    sto.write_object(f_table, f"{file}", output_file, wo_mode="o")
+                    sto.write(f_table, f"{file}", output_file, wo_mode="o")
                 # end file loop
 
             if log.getEffectiveLevel() >= logging.INFO:
@@ -1318,7 +1314,7 @@ def load_evts(
                                 )
                                 if os.path.exists(tier_path):
                                     table_name = self.filedb.get_table_name(tier, tb)
-                                    tier_table, _ = sto.read_object(
+                                    tier_table, _ = sto.read(
                                         table_name,
                                         tier_path,
                                         idx=idx_mask,
@@ -1332,7 +1328,7 @@ def load_evts(
                 if in_memory:
                     load_out[file] = f_table
                 if output_file:
-                    sto.write_object(f_table, f"file{file}", output_file, wo_mode="o")
+                    sto.write(f_table, f"file{file}", output_file, wo_mode="o")
                 # end file loop
 
             if in_memory:
diff --git a/src/pygama/flow/file_db.py b/src/pygama/flow/file_db.py
index c64e6b786..4047f8c97 100644
--- a/src/pygama/flow/file_db.py
+++ b/src/pygama/flow/file_db.py
@@ -9,11 +9,11 @@
 import warnings
 
 import h5py
-import lgdo
 import numpy as np
 import pandas as pd
-from lgdo import Array, Scalar, VectorOfVectors
-from lgdo import lh5_store as lh5
+from lgdo.lh5.store import LH5Store, ls
+from lgdo.lh5.utils import expand_path, expand_vars
+from lgdo.types import Array, Scalar, VectorOfVectors
 from parse import parse
 
 from . import utils
@@ -185,14 +185,12 @@ def set_config(self, config: dict, config_path: str = None) -> None:
         if config_path is not None:
             subst_vars["_"] = os.path.dirname(str(config_path))
 
-        data_dir = lgdo.lgdo_utils.expand_path(
-            self.config["data_dir"], substitute=subst_vars
-        )
+        data_dir = expand_path(self.config["data_dir"], substitute=subst_vars)
         self.data_dir = data_dir
 
         tier_dirs = self.config["tier_dirs"]
         for k, val in tier_dirs.items():
-            tier_dirs[k] = lgdo.lgdo_utils.expand_vars(val, substitute=subst_vars)
+            tier_dirs[k] = expand_vars(val, substitute=subst_vars)
         self.tier_dirs = tier_dirs
 
     def scan_files(self, dirs: list[str] = None) -> None:
@@ -407,7 +405,7 @@ def update_tables_cols(row, tier: str, utc_cache: dict = None) -> pd.Series:
                 )
 
                 # TODO this call here is really expensive!
-                groups = lh5.ls(f, wildcard)
+                groups = ls(f, wildcard)
                 if len(groups) > 0 and parse(template, groups[0]) is None:
                     log.warning(f"groups in {fpath} don't match template")
                 else:
@@ -431,7 +429,7 @@ def update_tables_cols(row, tier: str, utc_cache: dict = None) -> pd.Series:
                     table_name = template
 
                 try:
-                    col = lh5.ls(f[table_name])
+                    col = ls(f[table_name])
                 except KeyError:
                     log.warning(f"cannot find '{table_name}' in {fpath}")
                     continue
@@ -477,8 +475,8 @@ def update_tables_cols(row, tier: str, utc_cache: dict = None) -> pd.Series:
             columns_vov = VectorOfVectors(
                 flattened_data=flattened, cumulative_length=length
             )
-            sto = lh5.LH5Store()
-            sto.write_object(columns_vov, "unique_columns", to_file)
+            sto = LH5Store()
+            sto.write(columns_vov, "unique_columns", to_file)
 
         return self.columns
 
@@ -501,12 +499,12 @@ def from_disk(self, path: str | list[str]) -> None:
         # expand wildcards
         paths = []
         for p in path:
-            paths += lgdo.lgdo_utils.expand_path(p, list=True)
+            paths += expand_path(p, list=True)
 
         if not paths:
             raise FileNotFoundError(path)
 
-        sto = lh5.LH5Store()
+        sto = LH5Store()
         # objects/accumulators that will be used to configure the FileDB at the end
         _cfg = None
         _df = None
@@ -528,7 +526,7 @@ def _replace_idx(row, trans, tier):
 
         # loop over the files
         for p in paths:
-            cfg, _ = sto.read_object("config", p)
+            cfg, _ = sto.read("config", p)
             cfg = json.loads(cfg.value.decode())
 
             # make sure configurations are all the same
@@ -540,7 +538,7 @@ def _replace_idx(row, trans, tier):
                 )
 
             # read in unique columns
-            vov, _ = sto.read_object("columns", p)
+            vov, _ = sto.read("columns", p)
             # Convert back from VoV of UTF-8 bytestrings to a list of lists of strings
             columns = [[v.decode("utf-8") for v in ov] for ov in list(vov)]
 
@@ -599,14 +597,12 @@ def to_disk(self, filename: str, wo_mode="write_safe") -> None:
         filename
             output LH5 file name.
         wo_mode
-            passed to :meth:`~.lgdo.lh5_store.write_object`.
+            passed to :meth:`~.lgdo.lh5.write`.
         """
         log.debug(f"writing database to {filename}")
 
-        sto = lh5.LH5Store()
-        sto.write_object(
-            Scalar(json.dumps(self.config)), "config", filename, wo_mode=wo_mode
-        )
+        sto = LH5Store()
+        sto.write(Scalar(json.dumps(self.config)), "config", filename, wo_mode=wo_mode)
 
         if wo_mode in ["write_safe", "w", "overwrite_file", "of"]:
             wo_mode = "a"
@@ -623,7 +619,7 @@ def to_disk(self, filename: str, wo_mode="write_safe") -> None:
                 flattened_data=Array(nda=np.array(flat).astype("S")),
                 cumulative_length=Array(nda=np.array(cum_l)),
             )
-            sto.write_object(col_vov, "columns", filename, wo_mode=wo_mode)
+            sto.write(col_vov, "columns", filename, wo_mode=wo_mode)
 
         # FIXME: to_hdf() throws this:
         #
diff --git a/src/pygama/hit/build_hit.py b/src/pygama/hit/build_hit.py
index 5cc34202f..3f073380f 100644
--- a/src/pygama/hit/build_hit.py
+++ b/src/pygama/hit/build_hit.py
@@ -69,7 +69,7 @@ def build_hit(
     n_max
         maximum number of rows to process
     wo_mode
-        forwarded to :meth:`~.lgdo.lh5_store.write_object`.
+        forwarded to :meth:`~.lgdo.lh5.write`.
     """
     store = LH5Store()
 
@@ -168,7 +168,7 @@ def build_hit(
                         if col not in cfg["outputs"]:
                             outtbl_obj.remove_column(col, delete=True)
 
-            store.write_object(
+            store.write(
                 obj=outtbl_obj,
                 name=tbl.replace("/dsp", "/hit"),
                 lh5_file=outfile,
diff --git a/src/pygama/pargen/AoE_cal.py b/src/pygama/pargen/AoE_cal.py
index bbe0ee171..227aec4e2 100644
--- a/src/pygama/pargen/AoE_cal.py
+++ b/src/pygama/pargen/AoE_cal.py
@@ -15,7 +15,7 @@
 import matplotlib as mpl
 
 mpl.use("agg")
-import lgdo.lh5_store as lh5
+import lgdo.lh5 as lh5
 import matplotlib.cm as cmx
 import matplotlib.colors as mcolors
 import matplotlib.dates as mdates
diff --git a/src/pygama/pargen/cuts.py b/src/pygama/pargen/cuts.py
index e6c6b571e..c4ab158d7 100644
--- a/src/pygama/pargen/cuts.py
+++ b/src/pygama/pargen/cuts.py
@@ -9,7 +9,7 @@
 import logging
 import os
 
-import lgdo.lh5_store as lh5
+import lgdo.lh5 as lh5
 import numpy as np
 import pandas as pd
 from scipy import stats
diff --git a/src/pygama/pargen/ecal_th.py b/src/pygama/pargen/ecal_th.py
index bd957c3d4..e3526c63a 100644
--- a/src/pygama/pargen/ecal_th.py
+++ b/src/pygama/pargen/ecal_th.py
@@ -15,7 +15,7 @@
 from scipy.stats import binned_statistic
 
 mpl.use("agg")
-import lgdo.lh5_store as lh5
+import lgdo.lh5 as lh5
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
diff --git a/src/pygama/pargen/energy_optimisation.py b/src/pygama/pargen/energy_optimisation.py
index 24703fda2..1c34901d9 100644
--- a/src/pygama/pargen/energy_optimisation.py
+++ b/src/pygama/pargen/energy_optimisation.py
@@ -13,7 +13,7 @@
 import sys
 from collections import namedtuple
 
-import lgdo.lh5_store as lh5
+import lgdo.lh5 as lh5
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 import numpy as np
@@ -68,8 +68,8 @@ def run_optimisation(
         Number of events to run over
     """
     grid = set_par_space(opt_config)
-    waveforms = sto.read_object(f"/raw/{wf_field}", file, idx=cuts, n_rows=n_events)[0]
-    baseline = sto.read_object("/raw/baseline", file, idx=cuts, n_rows=n_events)[0]
+    waveforms = sto.read(f"/raw/{wf_field}", file, idx=cuts, n_rows=n_events)[0]
+    baseline = sto.read("/raw/baseline", file, idx=cuts, n_rows=n_events)[0]
     tb_data = lh5.Table(col_dict={f"{wf_field}": waveforms, "baseline": baseline})
     return opt.run_grid(tb_data, dsp_config, grid, fom, db_dict, **fom_kwargs)
 
@@ -138,12 +138,8 @@ def form_dict(in_dict, length):
             fom_kwargs = fom_kwargs["fom_kwargs"]
         fom_kwargs = form_dict(fom_kwargs, len(grid))
     sto = lh5.LH5Store()
-    waveforms = sto.read_object(
-        f"{lh5_path}/{wf_field}", file, idx=cuts, n_rows=n_events
-    )[0]
-    baseline = sto.read_object(f"{lh5_path}/baseline", file, idx=cuts, n_rows=n_events)[
-        0
-    ]
+    waveforms = sto.read(f"{lh5_path}/{wf_field}", file, idx=cuts, n_rows=n_events)[0]
+    baseline = sto.read(f"{lh5_path}/baseline", file, idx=cuts, n_rows=n_events)[0]
     tb_data = lh5.Table(col_dict={f"{wf_field}": waveforms, "baseline": baseline})
     return opt.run_grid_multiprocess_parallel(
         tb_data,
@@ -999,9 +995,7 @@ def event_selection(
     idx_list = get_wf_indexes(sort_index, idx_list_lens)
     idxs = np.array(sorted(np.concatenate(masks)))
 
-    input_data = sto.read_object(f"{lh5_path}", raw_files, idx=idxs, n_rows=len(idxs))[
-        0
-    ]
+    input_data = sto.read(f"{lh5_path}", raw_files, idx=idxs, n_rows=len(idxs))[0]
 
     if isinstance(dsp_config, str):
         with open(dsp_config) as r:
diff --git a/src/pygama/pargen/extract_tau.py b/src/pygama/pargen/extract_tau.py
index 72e357fd7..d35473715 100644
--- a/src/pygama/pargen/extract_tau.py
+++ b/src/pygama/pargen/extract_tau.py
@@ -15,7 +15,7 @@
 
 mpl.use("agg")
 import lgdo
-import lgdo.lh5_store as lh5
+import lgdo.lh5 as lh5
 import matplotlib.pyplot as plt
 import numpy as np
 
@@ -61,12 +61,10 @@ def load_data(
 
     cuts = np.where((df.daqenergy.values > threshold) & (~ids))[0]
 
-    waveforms = sto.read_object(
-        f"{lh5_path}/{wf_field}", raw_file, idx=cuts, n_rows=n_events
-    )[0]
-    baseline = sto.read_object(
-        f"{lh5_path}/baseline", raw_file, idx=cuts, n_rows=n_events
-    )[0]
+    waveforms = sto.read(f"{lh5_path}/{wf_field}", raw_file, idx=cuts, n_rows=n_events)[
+        0
+    ]
+    baseline = sto.read(f"{lh5_path}/baseline", raw_file, idx=cuts, n_rows=n_events)[0]
     tb_data = lh5.Table(col_dict={f"{wf_field}": waveforms, "baseline": baseline})
     return tb_data
 
diff --git a/src/pygama/pargen/utils.py b/src/pygama/pargen/utils.py
index 27f4af9ae..e58785e4e 100644
--- a/src/pygama/pargen/utils.py
+++ b/src/pygama/pargen/utils.py
@@ -69,7 +69,7 @@ def load_data(
         all_files = []
         masks = np.array([], dtype=bool)
         for tstamp, tfiles in files.items():
-            table = sto.read_object(lh5_path, tfiles)[0]
+            table = sto.read(lh5_path, tfiles)[0]
             if tstamp in cal_dict:
                 file_df = table.eval(cal_dict[tstamp]).get_dataframe()
             else:
@@ -95,7 +95,7 @@ def load_data(
         keys = [key.split("/")[-1] for key in keys]
         params = get_params(keys + list(cal_dict.keys()), params)
 
-        table = sto.read_object(lh5_path, files)[0]
+        table = sto.read(lh5_path, files)[0]
         df = table.eval(cal_dict).get_dataframe()
         for param in params:
             if param not in df:
diff --git a/tests/configs/icpc-dsp-config.json b/tests/configs/icpc-dsp-config.json
index 8536a31ec..28af29239 100644
--- a/tests/configs/icpc-dsp-config.json
+++ b/tests/configs/icpc-dsp-config.json
@@ -38,19 +38,19 @@
   "processors": {
     "tp_min, tp_max, wf_min, wf_max": {
       "function": "min_max",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["waveform", "tp_min", "tp_max", "wf_min", "wf_max"],
       "unit": ["ns", "ns", "ADC", "ADC"]
     },
     "wf_blsub": {
       "function": "bl_subtract",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["waveform", "baseline", "wf_blsub"],
       "unit": "ADC"
     },
     "bl_mean , bl_std, bl_slope, bl_intercept": {
       "function": "linear_slope_fit",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": [
         "wf_blsub[0:750]",
         "bl_mean",
@@ -62,51 +62,65 @@
     },
     "wf_pz": {
       "function": "pole_zero",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_blsub", "db.pz.tau", "wf_pz"],
       "unit": "ADC",
       "defaults": { "db.pz.tau": "27460.5" }
     },
     "pz_mean , pz_std, pz_slope, pz_intercept": {
       "function": "linear_slope_fit",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz[1500:]", "pz_mean", "pz_std", "pz_slope", "pz_intercept"],
       "unit": ["ADC", "ADC", "ADC", "ADC"]
     },
-    "wf_t0_filter": {
+    "t0_kernel": {
       "function": "t0_filter",
-      "module": "pygama.dsp.processors",
-      "args": ["wf_pz", "wf_t0_filter(len(wf_pz), 'f', grid=wf_pz.grid)"],
-      "init_args": ["128*ns/wf_pz.period", "2*us/wf_pz.period"],
+      "module": "dspeed.processors",
+      "args": [
+        "128*ns/wf_pz.period",
+        "2*us/wf_pz.period",
+        "t0_kernel(round((128*ns+2*us)/wf_pz.period), 'f')"
+      ],
+      "unit": "ADC"
+    },
+    "wf_t0_filter": {
+      "function": "convolve_wf",
+      "module": "dspeed.processors",
+      "args": [
+        "wf_pz",
+        "t0_kernel",
+        "'s'",
+        "wf_t0_filter(len(wf_pz), 'f', grid=wf_pz.grid)"
+      ],
       "unit": "ADC"
     },
     "wf_atrap": {
       "function": "asym_trap_filter",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "128*ns", "4", "2*us", "wf_atrap"],
       "unit": "ADC"
     },
     "conv_tmin ,tp_start, conv_min, conv_max": {
       "function": "min_max",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_t0_filter", "conv_tmin", "tp_start", "conv_min", "conv_max"],
       "unit": ["ns", "ns", "ADC", "ADC"]
     },
     "tp_0_atrap": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_atrap", "bl_std", "tp_start", 0, "tp_0_atrap"],
       "unit": "ns"
     },
     "tp_0_est": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_t0_filter", "bl_std", "tp_start", 0, "tp_0_est(unit=ns)"],
       "unit": "ns"
     },
     "wf_trap": {
       "function": "trap_norm",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "db.ttrap.rise", "db.ttrap.flat", "wf_trap"],
       "unit": "ADC",
       "defaults": { "db.ttrap.rise": "10*us", "db.ttrap.flat": "3.008*us" }
@@ -120,7 +134,7 @@
     },
     "wf_etrap": {
       "function": "trap_norm",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "db.etrap.rise", "db.etrap.flat", "wf_etrap"],
       "unit": "ADC",
       "defaults": { "db.etrap.rise": "10*us", "db.etrap.flat": "3.008*us" }
@@ -134,10 +148,10 @@
     },
     "trapEftp": {
       "function": "fixed_time_pickoff",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": [
         "wf_etrap",
-        "tp_0_est+db.etrap.rise+db.etrap.flat*db.etrap.sample",
+        "round(tp_0_est+db.etrap.rise+db.etrap.flat*db.etrap.sample, wf_etrap.grid)",
         "'l'",
         "trapEftp"
       ],
@@ -148,23 +162,33 @@
         "db.etrap.sample": "0.8"
       }
     },
-    "wf_cusp": {
+    "cusp_kernel": {
       "function": "cusp_filter",
-      "module": "pygama.dsp.processors",
-      "args": ["wf_blsub", "wf_cusp(101, 'f')"],
-      "init_args": [
-        "len(wf_blsub)-100",
+      "module": "dspeed.processors",
+      "args": [
         "db.cusp.sigma/wf_blsub.period",
         "round(db.cusp.flat/wf_blsub.period)",
-        "db.pz.tau"
+        "db.pz.tau/wf_blsub.period",
+        "cusp_kernel(round(len(wf_blsub)-(33.6*us/wf_blsub.period)-(4.8*us/wf_blsub.period)), 'f')"
       ],
       "defaults": {
         "db.cusp.sigma": "20*us",
         "db.cusp.flat": "3*us",
-        "db.pz.tau": "27460.5"
+        "db.pz.tau": "450*us"
       },
       "unit": "ADC"
     },
+    "wf_cusp": {
+      "function": "fft_convolve_wf",
+      "module": "dspeed.processors",
+      "args": [
+        "wf_blsub[:round(len(wf_blsub)-(33.6*us/wf_blsub.period))]",
+        "cusp_kernel",
+        "'v'",
+        "wf_cusp(round((4.8*us/wf_blsub.period)+1), 'f')"
+      ],
+      "unit": "ADC"
+    },
     "cuspEmax": {
       "function": "amax",
       "module": "numpy",
@@ -174,28 +198,38 @@
     },
     "cuspEftp": {
       "function": "fixed_time_pickoff",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_cusp", "db.cusp.sample", "'i'", "cuspEftp"],
       "unit": "ADC",
       "defaults": { "db.cusp.sample": "50" }
     },
-    "wf_zac": {
+    "zac_kernel": {
       "function": "zac_filter",
-      "module": "pygama.dsp.processors",
-      "args": ["wf_blsub", "wf_zac(101, 'f')"],
-      "init_args": [
-        "len(wf_blsub)-100",
+      "module": "dspeed.processors",
+      "args": [
         "db.zac.sigma/wf_blsub.period",
         "round(db.zac.flat/wf_blsub.period)",
-        "db.pz.tau"
+        "db.pz.tau/wf_blsub.period",
+        "zac_kernel(round(len(wf_blsub)-(33.6*us/wf_blsub.period)-(4.8*us/wf_blsub.period)), 'f')"
       ],
       "defaults": {
         "db.zac.sigma": "20*us",
         "db.zac.flat": "3*us",
-        "db.pz.tau": "27460.5"
+        "db.pz.tau": "450*us"
       },
       "unit": "ADC"
     },
+    "wf_zac": {
+      "function": "fft_convolve_wf",
+      "module": "dspeed.processors",
+      "args": [
+        "wf_blsub[:round(len(wf_blsub)-(33.6*us/wf_blsub.period))]",
+        "zac_kernel",
+        "'v'",
+        "wf_zac(round((4.8*us/wf_blsub.period)+1), 'f')"
+      ],
+      "unit": "ADC"
+    },
     "zacEmax": {
       "function": "amax",
       "module": "numpy",
@@ -205,74 +239,74 @@
     },
     "zacEftp": {
       "function": "fixed_time_pickoff",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_zac", "db.zac.sample", "'i'", "zacEftp"],
       "defaults": { "db.zac.sample": "50" },
       "unit": "ADC"
     },
     "tp_100": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax", "tp_0_est", 1, "tp_100"],
       "unit": "ns"
     },
     "tp_99": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "0.99*trapTmax", "tp_0_est", 1, "tp_99"],
       "unit": "ns"
     },
     "tp_95": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.95", "tp_99", 0, "tp_95"],
       "unit": "ns"
     },
     "tp_90": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.9", "tp_95", 0, "tp_90"],
       "unit": "ns"
     },
     "tp_80": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.8", "tp_90", 0, "tp_80"],
       "unit": "ns"
     },
     "tp_50": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.5", "tp_80", 0, "tp_50"],
       "unit": "ns"
     },
     "tp_20": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.2", "tp_50", 0, "tp_20"],
       "unit": "ns"
     },
     "tp_10": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.1", "tp_20", 0, "tp_10"],
       "unit": "ns"
     },
     "tp_01": {
       "function": "time_point_thresh",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "trapTmax*0.01", "tp_10", 0, "tp_01"],
       "unit": "ns"
     },
     "wf_trap2": {
       "function": "trap_norm",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "4*us", "96*ns", "wf_trap2"],
       "unit": "ADC"
     },
     "trapQftp": {
       "function": "fixed_time_pickoff",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_trap2", "tp_0_est + 8.096*us", "'l'", "trapQftp"],
       "unit": "ADC"
     },
@@ -290,31 +324,31 @@
     },
     "wf_le": {
       "function": "windower",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_pz", "tp_0_est", "wf_le(301, 'f')"],
       "unit": "ADC"
     },
     "curr": {
       "function": "avg_current",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["wf_le", 1, "curr(len(wf_le)-1, 'f')"],
       "unit": "ADC/sample"
     },
     "curr_up": {
       "function": "upsampler",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["curr", "16", "curr_up(4784, 'f')"],
       "unit": "ADC/sample"
     },
     "curr_av": {
       "function": "moving_window_multi",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["curr_up", "48", 3, 0, "curr_av"],
       "unit": "ADC/sample"
     },
     "aoe_t_min, tp_aoe_max, A_min, A_max": {
       "function": "min_max",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["curr_av", "aoe_t_min", "tp_aoe_max", "A_min", "A_max"],
       "unit": ["ns", "ns", "ADC/sample", "ADC/sample"]
     },
diff --git a/tests/configs/sipm-dplms-config.json b/tests/configs/sipm-dplms-config.json
index cc7919e33..dd69bac0f 100644
--- a/tests/configs/sipm-dplms-config.json
+++ b/tests/configs/sipm-dplms-config.json
@@ -10,26 +10,26 @@
   "processors": {
     "wf_gaus": {
       "function": "gaussian_filter1d",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.gaussian_filter1d",
       "args": ["waveform", "wf_gaus(len(waveform))"],
       "init_args": ["1", "4.0"],
       "unit": "ADC"
     },
     "curr": {
       "function": "avg_current",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.moving_windows",
       "args": ["wf_gaus", 5, "curr(len(wf_gaus)-5)"],
       "unit": "ADC"
     },
     "hist_weights , hist_borders": {
       "function": "histogram",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.histogram",
       "args": ["curr", "hist_weights(100)", "hist_borders(101)"],
       "unit": ["none", "ADC"]
     },
     "fwhm, idx_out_c, max_out": {
       "function": "histogram_stats",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.histogram",
       "args": [
         "hist_weights",
         "hist_borders",
@@ -42,7 +42,7 @@
     },
     "vt_max_candidate_out, vt_min_out, n_max_out, n_min_out": {
       "function": "get_multi_local_extrema",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.get_multi_local_extrema",
       "args": [
         "curr",
         5,
@@ -59,7 +59,7 @@
     },
     "trigger_pos, no_out": {
       "function": "peak_snr_threshold",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.peak_snr_threshold",
       "args": [
         "curr",
         "vt_max_candidate_out",
@@ -72,13 +72,13 @@
     },
     "energies": {
       "function": "multi_a_filter",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.multi_a_filter",
       "args": ["curr", "trigger_pos", "energies"],
       "unit": ["ADC"]
     },
     "bl_mean , bl_std, bl_slope, bl_intercept": {
       "function": "linear_slope_fit",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": [
         "waveform[:50]",
         "bl_mean",
@@ -90,34 +90,45 @@
     },
     "wf_diff": {
       "function": "avg_current",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors",
       "args": ["waveform", 1, "wf_diff(len(waveform)-1)"],
       "unit": "ADC"
     },
-    "wf_dplms": {
+    "dplms_kernel": {
       "function": "dplms_filter",
-      "module": "pygama.dsp.processors",
-      "args": ["wf_diff", "wf_dplms(len(wf_diff)-49, 'f')"],
-      "unit": "ADC",
-      "init_args": [
+      "module": "dspeed.processors",
+      "args": [
         "db.dplms.noise_matrix",
         "db.dplms.reference",
-        "50",
         "0.01",
         "1",
         "0",
-        "0"
-      ]
+        "0",
+        "dplms_kernel(50, 'f')"
+      ],
+      "unit": "ADC"
+    },
+    "wf_dplms": {
+      "description": "convolve optimised cusp filter",
+      "function": "convolve_wf",
+      "module": "dspeed.processors",
+      "args": [
+        "wf_diff",
+        "dplms_kernel",
+        "'s'",
+        "wf_dplms(len(wf_diff)-49, 'f')"
+      ],
+      "unit": "ADC"
     },
     "h_weights , h_borders": {
       "function": "histogram",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.histogram",
       "args": ["wf_dplms", "h_weights(100)", "h_borders(101)"],
       "unit": ["none", "ADC"]
     },
     "fwhm_d, idx_out_d, max_out_d": {
       "function": "histogram_stats",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.histogram",
       "args": [
         "h_weights",
         "h_borders",
@@ -130,7 +141,7 @@
     },
     "vt_max_candidate_out_d, vt_min_out_d, n_max_out_d, n_min_out_d": {
       "function": "get_multi_local_extrema",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.get_multi_local_extrema",
       "args": [
         "wf_dplms",
         10,
@@ -145,7 +156,7 @@
     },
     "trigger_pos_dplms, no_out_d": {
       "function": "peak_snr_threshold",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.peak_snr_threshold",
       "args": [
         "wf_dplms",
         "vt_max_candidate_out_d",
@@ -158,7 +169,7 @@
     },
     "energies_dplms": {
       "function": "multi_a_filter",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.multi_a_filter",
       "args": ["wf_dplms", "trigger_pos_dplms", "energies_dplms"],
       "unit": ["ADC"]
     }
diff --git a/tests/configs/sipm-dsp-config.json b/tests/configs/sipm-dsp-config.json
index 8de5bd2e6..bb7878a5d 100644
--- a/tests/configs/sipm-dsp-config.json
+++ b/tests/configs/sipm-dsp-config.json
@@ -3,26 +3,26 @@
   "processors": {
     "wf_gaus": {
       "function": "gaussian_filter1d",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.gaussian_filter1d",
       "args": ["waveform", "wf_gaus(len(waveform))"],
       "init_args": ["1", "4.0"],
       "unit": "ADC"
     },
     "curr": {
       "function": "avg_current",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.moving_windows",
       "args": ["wf_gaus", 5, "curr(len(wf_gaus)-5)"],
       "unit": "ADC"
     },
     "hist_weights , hist_borders": {
       "function": "histogram",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.histogram",
       "args": ["curr", "hist_weights(100)", "hist_borders(101)"],
       "unit": ["none", "ADC"]
     },
     "fwhm, idx_out_c, max_out": {
       "function": "histogram_stats",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.histogram",
       "args": [
         "hist_weights",
         "hist_borders",
@@ -35,7 +35,7 @@
     },
     "vt_max_candidate_out, vt_min_out, n_max_out, n_min_out": {
       "function": "get_multi_local_extrema",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.get_multi_local_extrema",
       "args": [
         "curr",
         5,
@@ -52,7 +52,7 @@
     },
     "trigger_pos, no_out": {
       "function": "peak_snr_threshold",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.peak_snr_threshold",
       "args": [
         "curr",
         "vt_max_candidate_out",
@@ -65,7 +65,7 @@
     },
     "energies": {
       "function": "multi_a_filter",
-      "module": "pygama.dsp.processors",
+      "module": "dspeed.processors.multi_a_filter",
       "args": ["curr", "trigger_pos", "energies"],
       "unit": ["ADC"]
     }
diff --git a/tests/evt/test_build_tcm.py b/tests/evt/test_build_tcm.py
index 505196825..49296e9fe 100644
--- a/tests/evt/test_build_tcm.py
+++ b/tests/evt/test_build_tcm.py
@@ -15,7 +15,7 @@ def test_generate_tcm_cols(lgnd_test_data):
     store = LH5Store()
     coin_data = []
     for tbl in tables:
-        ts, _ = store.read_object(f"{tbl}/raw/timestamp", f_raw)
+        ts, _ = store.read(f"{tbl}/raw/timestamp", f_raw)
         coin_data.append(ts)
 
     tcm_cols = evt.generate_tcm_cols(
@@ -67,6 +67,6 @@ def test_build_tcm(lgnd_test_data, tmptestdir):
     )
     assert os.path.exists(out_file)
     store = LH5Store()
-    obj, n_rows = store.read_object("hardware_tcm", out_file)
+    obj, n_rows = store.read("hardware_tcm", out_file)
     assert isinstance(obj, lgdo.Struct)
     assert list(obj.keys()) == ["cumulative_length", "array_id", "array_idx"]
diff --git a/tests/hit/test_build_hit.py b/tests/hit/test_build_hit.py
index 924928da6..8b8d39090 100644
--- a/tests/hit/test_build_hit.py
+++ b/tests/hit/test_build_hit.py
@@ -1,7 +1,7 @@
 import os
 from pathlib import Path
 
-import lgdo.lh5_store as store
+import lgdo.lh5 as store
 import numpy as np
 import pytest
 from lgdo import LH5Store, ls
@@ -94,7 +94,7 @@ def test_outputs_specification(dsp_test_file, tmptestdir):
     )
 
     store = LH5Store()
-    obj, _ = store.read_object("/geds/hit", outfile)
+    obj, _ = store.read("/geds/hit", outfile)
     assert list(obj.keys()) == ["calE", "AoE", "A_max"]
 
 
@@ -109,7 +109,7 @@ def test_aggregation_outputs(dsp_test_file, tmptestdir):
     )
 
     sto = LH5Store()
-    obj, _ = sto.read_object("/geds/hit", outfile)
+    obj, _ = sto.read("/geds/hit", outfile)
     assert list(obj.keys()) == [
         "is_valid_rt",
         "is_valid_t0",