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Fix performance issues #159

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8639203
fix from @llandsmeer
espenhgn Feb 21, 2022
87aa6a5
numba testing
espenhgn Feb 21, 2022
0d7a702
profiling notebook
espenhgn Feb 21, 2022
e29f0b0
not using cell.totnsegs attribute
espenhgn Feb 21, 2022
ae08111
test fastmath=True
espenhgn Feb 21, 2022
df6d5b9
reran cProfile script
espenhgn Feb 21, 2022
0470f71
use @njit decorator; parallelization test
espenhgn Feb 21, 2022
cb019a0
test with numba type hints
espenhgn Feb 21, 2022
62d5df3
cleanup that didn't solve anything
espenhgn Feb 21, 2022
f2a9f55
lfpcalc.calc_* methods no longer takes cell as input
espenhgn Feb 22, 2022
dc729a5
refactoring
espenhgn Feb 22, 2022
0e58f50
check vs. point sources
espenhgn Feb 22, 2022
3c1929b
roll back edits
espenhgn Feb 22, 2022
ed6bff5
fix
espenhgn Feb 22, 2022
392317f
fixed merge
espenhgn Mar 10, 2022
aa797d8
linting
espenhgn Mar 10, 2022
254682e
got rid of np.where
espenhgn Apr 1, 2022
311b93f
backup
espenhgn Apr 1, 2022
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283 changes: 283 additions & 0 deletions examples/cProfile.ipynb
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Original file line number Diff line number Diff line change
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "638c82eb-3757-4fe9-b1e8-0da9b736fa2d",
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6ac6cc3c-e07c-47da-a97f-a087621390ef",
"metadata": {},
"outputs": [],
"source": [
"import LFPy\n",
"import lfpykit\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "15b63f94-ebcd-42bf-8e80-9761def92965",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total number of segments: 3078\n"
]
}
],
"source": [
"# LFPy.Cell parameters\n",
"cellParameters = {\n",
" 'morphology': 'L5_Mainen96_LFPy.hoc', # morphology file\n",
" 'v_init': -65, # initial voltage\n",
" 'cm': 1.0, # membrane capacitance\n",
" 'Ra': 150, # axial resistivity\n",
" 'passive': True, # insert passive channels\n",
" 'passive_parameters': {\"g_pas\": 1. / 3E4,\n",
" \"e_pas\": -65}, # passive params\n",
" 'dt': 2**-4, # simulation time res\n",
" 'nsegs_method': 'lambda_f', # discretization rule\n",
" 'lambda_f': 1000 # frequency (Hz)\n",
"}\n",
"\n",
"# create LFPy.Cell instance\n",
"cell = LFPy.Cell(**cellParameters)\n",
"cell.set_rotation(x=4.98919, y=-4.33261, z=0.)\n",
"\n",
"print(f'total number of segments: {cell.totnsegs}')\n",
"\n",
"# parameters for line source potential\n",
"el_params = dict(\n",
" x = np.linspace(0, 1000, 1001),\n",
" y = np.zeros(1001),\n",
" z = np.zeros(1001),\n",
" sigma = 0.3\n",
")\n",
"\n",
"cell.simulate(rec_imem=True)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "3b8e2ec8-c8a4-48a6-81ef-b7dcee36c836",
"metadata": {},
"outputs": [],
"source": [
"# create line-source potential predictor\n",
"lsp = lfpykit.LineSourcePotential(cell, **el_params)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "79185fd5-9485-425c-8727-146c793126d9",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"OMP: Info #273: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"*** Profile printout saved to text file 'prun0'.\n"
]
}
],
"source": [
"%%prun -s cumulative -q -l 50 -T prun0\n",
"for i in range(100):\n",
" lsp.get_transformation_matrix()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "9fcd45b6-5349-4718-be60-ab8befe8dab0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 2670927 function calls (2651191 primitive calls) in 4.223 seconds\n",
"\n",
" Ordered by: cumulative time\n",
" List reduced from 1402 to 50 due to restriction <50>\n",
"\n",
" ncalls tottime percall cumtime percall filename:lineno(function)\n",
" 70/1 0.000 0.000 4.250 4.250 {built-in method builtins.exec}\n",
" 100 0.004 0.000 3.933 0.039 models.py:441(get_transformation_matrix)\n",
" 100 2.328 0.023 2.332 0.023 models.py:463(_get_transform)\n",
" 100 0.001 0.000 1.304 0.013 dispatcher.py:388(_compile_for_args)\n",
" 100 0.002 0.000 1.283 0.013 dispatcher.py:915(compile)\n",
" 100 0.000 0.000 1.269 0.013 caching.py:639(load_overload)\n",
"61409/61309 0.865 0.000 1.258 0.000 ffi.py:149(__call__)\n",
" 100 0.000 0.000 1.167 0.012 caching.py:650(_load_overload)\n",
" 100 0.000 0.000 1.116 0.011 caching.py:404(rebuild)\n",
" 100 0.001 0.000 1.116 0.011 compiler.py:210(_rebuild)\n",
" 100 0.000 0.000 1.088 0.011 codegen.py:1158(unserialize_library)\n",
" 100 0.000 0.000 1.087 0.011 codegen.py:926(_unserialize)\n",
" 100 0.000 0.000 0.509 0.005 module.py:29(parse_bitcode)\n",
" 200 0.002 0.000 0.509 0.003 codegen.py:1088(_load_defined_symbols)\n",
" 400 0.014 0.000 0.501 0.001 codegen.py:1092(<setcomp>)\n",
" 21100 0.008 0.000 0.315 0.000 ffi.py:356(__del__)\n",
" 21100 0.009 0.000 0.305 0.000 ffi.py:313(close)\n",
" 143 0.001 0.000 0.286 0.002 decorators.py:189(wrapper)\n",
" 100 0.001 0.000 0.282 0.003 module.py:76(_dispose)\n",
" 100 0.000 0.000 0.269 0.003 dispatcher.py:862(enable_caching)\n",
" 100 0.001 0.000 0.269 0.003 caching.py:610(__init__)\n",
" 100 0.001 0.000 0.267 0.003 caching.py:336(__init__)\n",
" 100 0.000 0.000 0.265 0.003 caching.py:186(from_function)\n",
" 100 0.000 0.000 0.260 0.003 caching.py:116(ensure_cache_path)\n",
" 100 0.000 0.000 0.256 0.003 tempfile.py:575(TemporaryFile)\n",
" 100 0.000 0.000 0.248 0.002 tempfile.py:244(_mkstemp_inner)\n",
" 100 0.245 0.002 0.245 0.002 {built-in method posix.open}\n",
" 61409 0.022 0.000 0.209 0.000 ffi.py:73(__exit__)\n",
" 61409 0.015 0.000 0.182 0.000 base.py:1260(exit_fn)\n",
" 61409 0.021 0.000 0.181 0.000 ffi.py:67(__enter__)\n",
" 20900 0.011 0.000 0.181 0.000 module.py:213(__next__)\n",
" 123018 0.042 0.000 0.171 0.000 event.py:193(broadcast)\n",
" 61509 0.033 0.000 0.168 0.000 event.py:388(end_event)\n",
" 20100 0.016 0.000 0.161 0.000 value.py:206(is_declaration)\n",
" 61409 0.014 0.000 0.155 0.000 base.py:1257(enter_fn)\n",
" 61509 0.032 0.000 0.141 0.000 event.py:374(start_event)\n",
" 15600 0.011 0.000 0.125 0.000 value.py:143(name)\n",
" 122818 0.045 0.000 0.121 0.000 event.py:227(notify)\n",
" 15000 0.009 0.000 0.114 0.000 module.py:233(_next)\n",
" 270/100 0.000 0.000 0.102 0.001 base.py:269(refresh)\n",
"1473/1436 0.003 0.000 0.082 0.000 <frozen importlib._bootstrap>:1022(_find_and_load)\n",
" 123018 0.037 0.000 0.073 0.000 event.py:84(__init__)\n",
"4640/4459 0.003 0.000 0.070 0.000 <frozen importlib._bootstrap>:1053(_handle_fromlist)\n",
" 73/36 0.000 0.000 0.066 0.002 <frozen importlib._bootstrap>:987(_find_and_load_unlocked)\n",
" 127/36 0.000 0.000 0.064 0.002 <frozen importlib._bootstrap>:233(_call_with_frames_removed)\n",
" 72/36 0.000 0.000 0.064 0.002 <frozen importlib._bootstrap>:664(_load_unlocked)\n",
" 69/35 0.000 0.000 0.063 0.002 <frozen importlib._bootstrap_external>:877(exec_module)\n",
" 270 0.003 0.000 0.062 0.000 cpu.py:69(load_additional_registries)\n",
" 100 0.000 0.000 0.058 0.001 codegen.py:782(_finalize_final_module)\n",
" 52/33 0.000 0.000 0.057 0.002 {built-in method builtins.__import__}\n"
]
}
],
"source": [
"print(open('prun0', 'r').read())"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "045d95d5-f58a-4ee3-a591-ea2bf241269e",
"metadata": {},
"outputs": [],
"source": [
"# create point-source potential predictor\n",
"psp = lfpykit.PointSourcePotential(cell, **el_params)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a6d382dd-d4c6-4bab-9147-3cd5b189a700",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
"*** Profile printout saved to text file 'prun1'.\n"
]
}
],
"source": [
"%%prun -s cumulative -q -l 20 -T prun1\n",
"for i in range(100):\n",
" psp.get_transformation_matrix()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "2531c6fd-935f-4907-89a9-aef29e73f277",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 3203403 function calls in 8.508 seconds\n",
"\n",
" Ordered by: cumulative time\n",
"\n",
" ncalls tottime percall cumtime percall filename:lineno(function)\n",
" 1 0.000 0.000 8.508 8.508 {built-in method builtins.exec}\n",
" 1 0.010 0.010 8.508 8.508 <string>:1(<module>)\n",
" 100 0.232 0.002 8.498 0.085 models.py:279(get_transformation_matrix)\n",
" 100100 1.279 0.000 8.266 0.000 lfpcalc.py:604(calc_lfp_pointsource)\n",
" 300300 0.065 0.000 6.647 0.000 {method 'mean' of 'numpy.ndarray' objects}\n",
" 300300 0.806 0.000 6.582 0.000 _methods.py:162(_mean)\n",
" 300300 5.484 0.000 5.484 0.000 {method 'reduce' of 'numpy.ufunc' objects}\n",
" 100100 0.340 0.000 0.340 0.000 lfpcalc.py:686(_check_rlimit_point)\n",
" 300300 0.210 0.000 0.245 0.000 _methods.py:66(_count_reduce_items)\n",
" 600600 0.026 0.000 0.026 0.000 {built-in method builtins.issubclass}\n",
" 600600 0.026 0.000 0.026 0.000 {built-in method builtins.isinstance}\n",
" 300300 0.019 0.000 0.019 0.000 {built-in method numpy.core._multiarray_umath.normalize_axis_index}\n",
" 300300 0.011 0.000 0.011 0.000 {built-in method numpy.asanyarray}\n",
" 100 0.000 0.000 0.000 0.000 {built-in method numpy.empty}\n",
" 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}\n"
]
}
],
"source": [
"print(open('prun1', 'r').read())"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "281b24fe-12ed-40eb-a56e-2983c2a8806a",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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