add Benchmark (pytest) benchmark result for 466aed65269e4d9d17a4f4e5b737d3184d60e679
diff --git a/dev/bench/data.js b/dev/bench/data.js index 206e49a..2ca446b 100644 --- a/dev/bench/data.js +++ b/dev/bench/data.js
@@ -1,5 +1,5 @@ window.BENCHMARK_DATA = { - "lastUpdate": 1720643492025, + "lastUpdate": 1720644423899, "repoUrl": "https://github.com/MPACT-ORG/mpact-compiler", "entries": { "Benchmark": [ @@ -742,6 +742,114 @@ "extra": "mean: 47.29601163156578 msec\nrounds: 19" } ] + }, + { + "commit": { + "author": { + "email": "ajcbik@google.com", + "name": "Aart Bik", + "username": "aartbik" + }, + "committer": { + "email": "noreply@github.com", + "name": "GitHub", + "username": "web-flow" + }, + "distinct": true, + "id": "466aed65269e4d9d17a4f4e5b737d3184d60e679", + "message": "[mpact][compiler] only import what you need in tests (#61)", + "timestamp": "2024-07-10T13:42:27-07:00", + "tree_id": "a96ce0dcd9a60503583756c90cf7c618d31f2fdf", + "url": "https://github.com/MPACT-ORG/mpact-compiler/commit/466aed65269e4d9d17a4f4e5b737d3184d60e679" + }, + "date": 1720644423077, + "tool": "pytest", + "benches": [ + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mv_dense", + "value": 5892.849972887261, + "unit": "iter/sec", + "range": "stddev: 0.000004959268193198534", + "extra": "mean: 169.69717617128472 usec\nrounds: 1771" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mm_dense", + "value": 34.68541262005039, + "unit": "iter/sec", + "range": "stddev: 0.00044738449261459793", + "extra": "mean: 28.830563757570403 msec\nrounds: 33" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_add_dense", + "value": 5806.271338374302, + "unit": "iter/sec", + "range": "stddev: 0.00004927253595346353", + "extra": "mean: 172.2275694197905 usec\nrounds: 2204" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mul_dense", + "value": 5826.095561160015, + "unit": "iter/sec", + "range": "stddev: 0.00003290846321017504", + "extra": "mean: 171.6415375447246 usec\nrounds: 3609" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_nop_dense", + "value": 966125.627784602, + "unit": "iter/sec", + "range": "stddev: 1.838781261933848e-7", + "extra": "mean: 1.035062078099589 usec\nrounds: 144447" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_sddmm_dense", + "value": 31.13639062389227, + "unit": "iter/sec", + "range": "stddev: 0.00043796326986517375", + "extra": "mean: 32.11676048387759 msec\nrounds: 31" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mv_sparse", + "value": 12356.607210939963, + "unit": "iter/sec", + "range": "stddev: 0.000003996111306778252", + "extra": "mean: 80.92836350051223 usec\nrounds: 3326" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mm_sparse", + "value": 19.92411439930273, + "unit": "iter/sec", + "range": "stddev: 0.001130257434495826", + "extra": "mean: 50.19043657142404 msec\nrounds: 21" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_add_sparse", + "value": 204.3538353123811, + "unit": "iter/sec", + "range": "stddev: 0.0006957100557737918", + "extra": "mean: 4.893473119657243 msec\nrounds: 234" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mul_sparse", + "value": 188.81403914912207, + "unit": "iter/sec", + "range": "stddev: 0.00020072138852544395", + "extra": "mean: 5.296216343373795 msec\nrounds: 166" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_nop_sparse", + "value": 971022.1186577489, + "unit": "iter/sec", + "range": "stddev: 1.9237787835734797e-7", + "extra": "mean: 1.0298426583549996 usec\nrounds: 196890" + }, + { + "name": "benchmark/python/benchmarks/regression_benchmark.py::test_sddmm_sparse", + "value": 19.598736962010374, + "unit": "iter/sec", + "range": "stddev: 0.0033167102573383195", + "extra": "mean: 51.02369616666477 msec\nrounds: 18" + } + ] } ] }