Benchmark internal STARDIS functions #85

light2802 · 2023-07-10T18:19:07Z

📝 Description

Type: 🪲 bugfix | 🚀 feature | 🚦 testing 🎢 infrastructure

This PR adds workflow to benchmark internal stardis functions like raytrace

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Examples, notebooks, and links to useful references.

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light2802 · 2023-07-12T09:21:23Z

This PR is based on top of PR #85 . So lets merge that first

jvshields · 2023-07-12T12:56:47Z

This PR is based on top of PR #85 . So lets merge that first

Sorry, do you mean 74? 85 is this PR.

light2802 · 2023-07-12T13:05:28Z

This PR is based on top of PR #85 . So lets merge that first

Sorry, do you mean 74? 85 is this PR.

Sorry , yes PR #74

benchmarks/run_stardis.py

codecov · 2023-07-17T17:46:48Z

Codecov Report

Merging #85 (7e5e053) into main (437e371) will not change coverage.
The diff coverage is n/a.

❗ Current head 7e5e053 differs from pull request most recent head 1474791. Consider uploading reports for the commit 1474791 to get more accurate results

@@           Coverage Diff           @@
##             main      #85   +/-   ##
=======================================
  Coverage   33.89%   33.89%           
=======================================
  Files          17       17           
  Lines         658      658           
=======================================
  Hits          223      223           
  Misses        435      435

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atharva-2001 · 2023-08-07T08:38:10Z

I think this needs a rebase @light2802

tardis-bot · 2023-08-09T14:48:38Z

*beep* *bop*
Hi human,
I ran benchmarks as you asked comparing main (437e371) and the latest commit (1474791).
Here are the logs produced by ASV.
Results can also be downloaded as artifacts here.
Significantly changed benchmarks:

All benchmarks:

All benchmarks:

     before           after         ratio
   [437e3711]       [1474791c]
     10.3±0.01s       10.3±0.09s     1.00  run_stardis.BenchmarkStardis.time_calc_alpha
      206±0.7ms          201±2ms     0.97  run_stardis.BenchmarkStardis.time_raytrace
         failed           failed      n/a  run_stardis.BenchmarkStardis.time_run_stardis

* setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * removing copied files * add back voigt test * further clean up stardis/base.py * remove transport files * update documentation * Add CUDA GPU JIT compilation to `faddeeva()` (#107) * Add cuda import * Add cuda boilerplate for faddeeva * Add square root of pi as constant to scope of entire file * Add faddeeva_cuda test * Vectorize faddeeva * Refactor faddeeva to be vectorized and work with cuda * Clean up faddeeva_cuda test * Rename variables to keep with convention * Refactor faddeeva_gpu and include associated tests * Add functionality for more datatypes for faddeeva_cuda Also add associated tests * Clean up faddeeva_gpu tests by testing numpy and cuda array types separately * Optimize faddeeva function to be branchless * Use cupy arrays instead of numba.cuda arrays Also call faddeeva_cuda with prespecified numbers of blocks and threads * Only import cupy if the machine has GPUs available * Typecast input to complex * Size should be of output array * Return cupy array by default * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * add units to stardis outputs (#122) * add units to stardis outputs * explicitly declare units to F_lambda * Benchmark internal STARDIS functions (#85) * Fix posting comment * Try addding token as env var * Put env var at correct place * fix benchmark comment bug * Benchmark raytrace function * Correct path for config soft link * Increase timeout time for raytrace benchmark * Add code to benchmark calc_alpha_line_at_nu * Add push trigger for all branches temporarily * Group all the benchmarking code under one class * Add tracing_lambdas attribute to benchmark class * Update benchmark setup * Fix breaking benchmark pipeline (#128) * Refactor and add CUDA JIT compilation to `voigt_profile()` (#113) * Add pi as a constant with file scope * Use real attribute of datatype rather than numpy call * Vectorize voigt_profile and add tests * Change indenting to improve readability * Typecast inputs to float and remove tests that include complex inputs * Add cuda versions of voigt_profile along with associated tests * Return cupy array by default * Size should be of output array * Fix typo in mathematical formula for `voigt_profile()` * Fix unit tests * Add CUDA JIT to `calc_n_effective()` (#119) * Add basic test for `calc_doppler_width()` * Refactor `calc_doppler_width()` and add test for vectorized implementation * Typecast to float * Add unwrapped cuda implementation of doppler_width Also typecast all global constants to float * Add wrapped cuda implementation of calc_doppler_width * Return cupy array by default * Add test for `calc_n_effective()` * Typecast inputs and refactor * Add cuda implementations and tests for `calc_n_effective()` * Return cupy array by default * Revert changes to `voigt_profile()` formula (#131) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * add back voigt test * removing copied files * further clean up stardis/base.py * remove transport files * update documentation * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * fix imports * fix broadening merge * apply black * change benchmark paths --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]>

* setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * removing copied files * add back voigt test * further clean up stardis/base.py * remove transport files * update documentation * Add CUDA GPU JIT compilation to `faddeeva()` (tardis-sn#107) * Add cuda import * Add cuda boilerplate for faddeeva * Add square root of pi as constant to scope of entire file * Add faddeeva_cuda test * Vectorize faddeeva * Refactor faddeeva to be vectorized and work with cuda * Clean up faddeeva_cuda test * Rename variables to keep with convention * Refactor faddeeva_gpu and include associated tests * Add functionality for more datatypes for faddeeva_cuda Also add associated tests * Clean up faddeeva_gpu tests by testing numpy and cuda array types separately * Optimize faddeeva function to be branchless * Use cupy arrays instead of numba.cuda arrays Also call faddeeva_cuda with prespecified numbers of blocks and threads * Only import cupy if the machine has GPUs available * Typecast input to complex * Size should be of output array * Return cupy array by default * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * add units to stardis outputs (tardis-sn#122) * add units to stardis outputs * explicitly declare units to F_lambda * Benchmark internal STARDIS functions (tardis-sn#85) * Fix posting comment * Try addding token as env var * Put env var at correct place * fix benchmark comment bug * Benchmark raytrace function * Correct path for config soft link * Increase timeout time for raytrace benchmark * Add code to benchmark calc_alpha_line_at_nu * Add push trigger for all branches temporarily * Group all the benchmarking code under one class * Add tracing_lambdas attribute to benchmark class * Update benchmark setup * Fix breaking benchmark pipeline (tardis-sn#128) * Refactor and add CUDA JIT compilation to `voigt_profile()` (tardis-sn#113) * Add pi as a constant with file scope * Use real attribute of datatype rather than numpy call * Vectorize voigt_profile and add tests * Change indenting to improve readability * Typecast inputs to float and remove tests that include complex inputs * Add cuda versions of voigt_profile along with associated tests * Return cupy array by default * Size should be of output array * Fix typo in mathematical formula for `voigt_profile()` * Fix unit tests * Add CUDA JIT to `calc_n_effective()` (tardis-sn#119) * Add basic test for `calc_doppler_width()` * Refactor `calc_doppler_width()` and add test for vectorized implementation * Typecast to float * Add unwrapped cuda implementation of doppler_width Also typecast all global constants to float * Add wrapped cuda implementation of calc_doppler_width * Return cupy array by default * Add test for `calc_n_effective()` * Typecast inputs and refactor * Add cuda implementations and tests for `calc_n_effective()` * Return cupy array by default * Revert changes to `voigt_profile()` formula (tardis-sn#131) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * add back voigt test * removing copied files * further clean up stardis/base.py * remove transport files * update documentation * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * fix imports * fix broadening merge * apply black * change benchmark paths --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]>

* Restructure: Add radiation field (#123) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * removing copied files * add back voigt test * further clean up stardis/base.py * remove transport files * update documentation * Add CUDA GPU JIT compilation to `faddeeva()` (#107) * Add cuda import * Add cuda boilerplate for faddeeva * Add square root of pi as constant to scope of entire file * Add faddeeva_cuda test * Vectorize faddeeva * Refactor faddeeva to be vectorized and work with cuda * Clean up faddeeva_cuda test * Rename variables to keep with convention * Refactor faddeeva_gpu and include associated tests * Add functionality for more datatypes for faddeeva_cuda Also add associated tests * Clean up faddeeva_gpu tests by testing numpy and cuda array types separately * Optimize faddeeva function to be branchless * Use cupy arrays instead of numba.cuda arrays Also call faddeeva_cuda with prespecified numbers of blocks and threads * Only import cupy if the machine has GPUs available * Typecast input to complex * Size should be of output array * Return cupy array by default * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * add units to stardis outputs (#122) * add units to stardis outputs * explicitly declare units to F_lambda * Benchmark internal STARDIS functions (#85) * Fix posting comment * Try addding token as env var * Put env var at correct place * fix benchmark comment bug * Benchmark raytrace function * Correct path for config soft link * Increase timeout time for raytrace benchmark * Add code to benchmark calc_alpha_line_at_nu * Add push trigger for all branches temporarily * Group all the benchmarking code under one class * Add tracing_lambdas attribute to benchmark class * Update benchmark setup * Fix breaking benchmark pipeline (#128) * Refactor and add CUDA JIT compilation to `voigt_profile()` (#113) * Add pi as a constant with file scope * Use real attribute of datatype rather than numpy call * Vectorize voigt_profile and add tests * Change indenting to improve readability * Typecast inputs to float and remove tests that include complex inputs * Add cuda versions of voigt_profile along with associated tests * Return cupy array by default * Size should be of output array * Fix typo in mathematical formula for `voigt_profile()` * Fix unit tests * Add CUDA JIT to `calc_n_effective()` (#119) * Add basic test for `calc_doppler_width()` * Refactor `calc_doppler_width()` and add test for vectorized implementation * Typecast to float * Add unwrapped cuda implementation of doppler_width Also typecast all global constants to float * Add wrapped cuda implementation of calc_doppler_width * Return cupy array by default * Add test for `calc_n_effective()` * Typecast inputs and refactor * Add cuda implementations and tests for `calc_n_effective()` * Return cupy array by default * Revert changes to `voigt_profile()` formula (#131) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * add back voigt test * removing copied files * further clean up stardis/base.py * remove transport files * update documentation * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * fix imports * fix broadening merge * apply black * change benchmark paths --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]> * fix voigt test that got overwritten by the rebase * add black to voigt.py * include fixto voight profile from pr 131 * fix benchmarks * further fix of benchmarks * remove blackbody import comment in radiation_field_solvers/base.py --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]>

* Fix posting comment * Try addding token as env var * Put env var at correct place * fix benchmark comment bug * Benchmark raytrace function * Correct path for config soft link * Increase timeout time for raytrace benchmark * Add code to benchmark calc_alpha_line_at_nu * Add push trigger for all branches temporarily * Group all the benchmarking code under one class * Add tracing_lambdas attribute to benchmark class * Update benchmark setup

* setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * removing copied files * add back voigt test * further clean up stardis/base.py * remove transport files * update documentation * Add CUDA GPU JIT compilation to `faddeeva()` (tardis-sn#107) * Add cuda import * Add cuda boilerplate for faddeeva * Add square root of pi as constant to scope of entire file * Add faddeeva_cuda test * Vectorize faddeeva * Refactor faddeeva to be vectorized and work with cuda * Clean up faddeeva_cuda test * Rename variables to keep with convention * Refactor faddeeva_gpu and include associated tests * Add functionality for more datatypes for faddeeva_cuda Also add associated tests * Clean up faddeeva_gpu tests by testing numpy and cuda array types separately * Optimize faddeeva function to be branchless * Use cupy arrays instead of numba.cuda arrays Also call faddeeva_cuda with prespecified numbers of blocks and threads * Only import cupy if the machine has GPUs available * Typecast input to complex * Size should be of output array * Return cupy array by default * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * add units to stardis outputs (tardis-sn#122) * add units to stardis outputs * explicitly declare units to F_lambda * Benchmark internal STARDIS functions (tardis-sn#85) * Fix posting comment * Try addding token as env var * Put env var at correct place * fix benchmark comment bug * Benchmark raytrace function * Correct path for config soft link * Increase timeout time for raytrace benchmark * Add code to benchmark calc_alpha_line_at_nu * Add push trigger for all branches temporarily * Group all the benchmarking code under one class * Add tracing_lambdas attribute to benchmark class * Update benchmark setup * Fix breaking benchmark pipeline (tardis-sn#128) * Refactor and add CUDA JIT compilation to `voigt_profile()` (tardis-sn#113) * Add pi as a constant with file scope * Use real attribute of datatype rather than numpy call * Vectorize voigt_profile and add tests * Change indenting to improve readability * Typecast inputs to float and remove tests that include complex inputs * Add cuda versions of voigt_profile along with associated tests * Return cupy array by default * Size should be of output array * Fix typo in mathematical formula for `voigt_profile()` * Fix unit tests * Add CUDA JIT to `calc_n_effective()` (tardis-sn#119) * Add basic test for `calc_doppler_width()` * Refactor `calc_doppler_width()` and add test for vectorized implementation * Typecast to float * Add unwrapped cuda implementation of doppler_width Also typecast all global constants to float * Add wrapped cuda implementation of calc_doppler_width * Return cupy array by default * Add test for `calc_n_effective()` * Typecast inputs and refactor * Add cuda implementations and tests for `calc_n_effective()` * Return cupy array by default * Revert changes to `voigt_profile()` formula (tardis-sn#131) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * add back voigt test * removing copied files * further clean up stardis/base.py * remove transport files * update documentation * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * fix imports * fix broadening merge * apply black * change benchmark paths --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]>

* Restructure: Add radiation field (tardis-sn#123) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * removing copied files * add back voigt test * further clean up stardis/base.py * remove transport files * update documentation * Add CUDA GPU JIT compilation to `faddeeva()` (tardis-sn#107) * Add cuda import * Add cuda boilerplate for faddeeva * Add square root of pi as constant to scope of entire file * Add faddeeva_cuda test * Vectorize faddeeva * Refactor faddeeva to be vectorized and work with cuda * Clean up faddeeva_cuda test * Rename variables to keep with convention * Refactor faddeeva_gpu and include associated tests * Add functionality for more datatypes for faddeeva_cuda Also add associated tests * Clean up faddeeva_gpu tests by testing numpy and cuda array types separately * Optimize faddeeva function to be branchless * Use cupy arrays instead of numba.cuda arrays Also call faddeeva_cuda with prespecified numbers of blocks and threads * Only import cupy if the machine has GPUs available * Typecast input to complex * Size should be of output array * Return cupy array by default * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * add units to stardis outputs (tardis-sn#122) * add units to stardis outputs * explicitly declare units to F_lambda * Benchmark internal STARDIS functions (tardis-sn#85) * Fix posting comment * Try addding token as env var * Put env var at correct place * fix benchmark comment bug * Benchmark raytrace function * Correct path for config soft link * Increase timeout time for raytrace benchmark * Add code to benchmark calc_alpha_line_at_nu * Add push trigger for all branches temporarily * Group all the benchmarking code under one class * Add tracing_lambdas attribute to benchmark class * Update benchmark setup * Fix breaking benchmark pipeline (tardis-sn#128) * Refactor and add CUDA JIT compilation to `voigt_profile()` (tardis-sn#113) * Add pi as a constant with file scope * Use real attribute of datatype rather than numpy call * Vectorize voigt_profile and add tests * Change indenting to improve readability * Typecast inputs to float and remove tests that include complex inputs * Add cuda versions of voigt_profile along with associated tests * Return cupy array by default * Size should be of output array * Fix typo in mathematical formula for `voigt_profile()` * Fix unit tests * Add CUDA JIT to `calc_n_effective()` (tardis-sn#119) * Add basic test for `calc_doppler_width()` * Refactor `calc_doppler_width()` and add test for vectorized implementation * Typecast to float * Add unwrapped cuda implementation of doppler_width Also typecast all global constants to float * Add wrapped cuda implementation of calc_doppler_width * Return cupy array by default * Add test for `calc_n_effective()` * Typecast inputs and refactor * Add cuda implementations and tests for `calc_n_effective()` * Return cupy array by default * Revert changes to `voigt_profile()` formula (tardis-sn#131) * setting up radiation field structure * further work moving structures around * hook up radiation field to run_stardis() * fix bug with output * add back voigt test * removing copied files * further clean up stardis/base.py * remove transport files * update documentation * Change name of blackbody function. Hook up RadiationField.source_function to raytrace. * fix imports * fix broadening merge * apply black * change benchmark paths --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]> * fix voigt test that got overwritten by the rebase * add black to voigt.py * include fixto voight profile from pr 131 * fix benchmarks * further fix of benchmarks * remove blackbody import comment in radiation_field_solvers/base.py --------- Co-authored-by: smokestacklightnin <[email protected]> Co-authored-by: light2802 <[email protected]>

light2802 force-pushed the internal_func branch 12 times, most recently from 8baec7b to 94520da Compare July 12, 2023 07:51

light2802 added the benchmarks Trigger benchmarks to run on this pr label Jul 12, 2023

light2802 force-pushed the internal_func branch 2 times, most recently from ffb1e29 to 8ecc43a Compare July 12, 2023 08:35

light2802 marked this pull request as ready for review July 12, 2023 09:20

light2802 requested review from wkerzendorf, jvshields and atharva-2001 July 12, 2023 09:21

jvshields reviewed Jul 17, 2023

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jvshields previously approved these changes Aug 3, 2023

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light2802 dismissed jvshields’s stale review via d518658 August 7, 2023 12:09

light2802 force-pushed the internal_func branch from f55da6f to d518658 Compare August 7, 2023 12:09

light2802 force-pushed the internal_func branch from 84c257f to 8014910 Compare August 9, 2023 18:17

light2802 added 12 commits August 10, 2023 22:54

Fix posting comment

3c10631

Try addding token as env var

fdc2573

Put env var at correct place

fd21405

fix benchmark comment bug

d71f6ea

Benchmark raytrace function

c2aff07

Correct path for config soft link

33bcd56

Increase timeout time for raytrace benchmark

1f3952f

Add code to benchmark calc_alpha_line_at_nu

aa8c01b

Add push trigger for all branches temporarily

6ad0375

Group all the benchmarking code under one class

f2159da

Add tracing_lambdas attribute to benchmark class

4b14b3a

Update benchmark setup

1474791

light2802 force-pushed the internal_func branch from 8014910 to 1474791 Compare August 10, 2023 17:43

jvshields approved these changes Aug 11, 2023

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jvshields mentioned this pull request Aug 11, 2023

Add next term van noort intensity solver #120

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atharva-2001 approved these changes Aug 18, 2023

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andrewfullard merged commit 384031f into tardis-sn:main Aug 18, 2023
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Benchmark internal STARDIS functions #85

Benchmark internal STARDIS functions #85

light2802 commented Jul 10, 2023

light2802 commented Jul 12, 2023

jvshields commented Jul 12, 2023

light2802 commented Jul 12, 2023

codecov bot commented Jul 17, 2023 •

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atharva-2001 commented Aug 7, 2023

tardis-bot commented Aug 9, 2023 •

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Benchmark internal STARDIS functions #85

Benchmark internal STARDIS functions #85

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light2802 commented Jul 10, 2023

📝 Description

📌 Resources

🚦 Testing

☑️ Checklist

light2802 commented Jul 12, 2023

jvshields commented Jul 12, 2023

light2802 commented Jul 12, 2023

codecov bot commented Jul 17, 2023 • edited Loading

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