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"
+ }
+ ]
}
]
}
