| window.BENCHMARK_DATA = { |
| "lastUpdate": 1719528536364, |
| "repoUrl": "https://github.com/MPACT-ORG/mpact-compiler", |
| "entries": { |
| "Benchmark": [ |
| { |
| "commit": { |
| "author": { |
| "name": "MPACT-ORG", |
| "username": "MPACT-ORG" |
| }, |
| "committer": { |
| "name": "MPACT-ORG", |
| "username": "MPACT-ORG" |
| }, |
| "id": "86dff1a36cbd620f2d73af763e949ec00d777239", |
| "message": "[mpact][benchmark] add regression benchmark to gh page", |
| "timestamp": "2024-06-27T22:22:10Z", |
| "url": "https://github.com/MPACT-ORG/mpact-compiler/pull/52/commits/86dff1a36cbd620f2d73af763e949ec00d777239" |
| }, |
| "date": 1719528535086, |
| "tool": "pytest", |
| "benches": [ |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mv_dense", |
| "value": 6669.427405418031, |
| "unit": "iter/sec", |
| "range": "stddev: 0.000005968668091106435", |
| "extra": "mean: 149.93790909061124 usec\nrounds: 2057" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mm_dense", |
| "value": 34.302140003556715, |
| "unit": "iter/sec", |
| "range": "stddev: 0.0003297513733362601", |
| "extra": "mean: 29.15270009090722 msec\nrounds: 33" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_add_dense", |
| "value": 5915.897194757258, |
| "unit": "iter/sec", |
| "range": "stddev: 0.00003919411579877867", |
| "extra": "mean: 169.03606791649665 usec\nrounds: 1973" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mul_dense", |
| "value": 6002.4939914783945, |
| "unit": "iter/sec", |
| "range": "stddev: 0.000027105251732015887", |
| "extra": "mean: 166.59741790990168 usec\nrounds: 3551" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_nop_dense", |
| "value": 948864.5687594158, |
| "unit": "iter/sec", |
| "range": "stddev: 1.8437976818208762e-7", |
| "extra": "mean: 1.0538911799683288 usec\nrounds: 144238" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_sddmm_dense", |
| "value": 32.142115430220215, |
| "unit": "iter/sec", |
| "range": "stddev: 0.000630869582999464", |
| "extra": "mean: 31.111829032254484 msec\nrounds: 31" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mv_sparse", |
| "value": 12377.336292065489, |
| "unit": "iter/sec", |
| "range": "stddev: 0.000005090184458909657", |
| "extra": "mean: 80.79282782686057 usec\nrounds: 3299" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mm_sparse", |
| "value": 20.396281430385955, |
| "unit": "iter/sec", |
| "range": "stddev: 0.0003606405379378096", |
| "extra": "mean: 49.02854490476979 msec\nrounds: 21" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_add_sparse", |
| "value": 210.87200147418721, |
| "unit": "iter/sec", |
| "range": "stddev: 0.0005598196294447149", |
| "extra": "mean: 4.742213252632355 msec\nrounds: 285" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_mul_sparse", |
| "value": 189.26652258818748, |
| "unit": "iter/sec", |
| "range": "stddev: 0.00010650763765171751", |
| "extra": "mean: 5.2835545680512865 msec\nrounds: 169" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_nop_sparse", |
| "value": 1093738.9035266023, |
| "unit": "iter/sec", |
| "range": "stddev: 8.140592632863567e-8", |
| "extra": "mean: 914.2949901257589 nsec\nrounds: 177589" |
| }, |
| { |
| "name": "benchmark/python/benchmarks/regression_benchmark.py::test_sddmm_sparse", |
| "value": 21.33905041385192, |
| "unit": "iter/sec", |
| "range": "stddev: 0.002583893132946909", |
| "extra": "mean: 46.862441421051486 msec\nrounds: 19" |
| } |
| ] |
| } |
| ] |
| } |
| } |
