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December 27, 2023 05:52
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pathfinding: PGO Instrumented compared to Release
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| cargo pgo bench | |
| Running benches/algos.rs (x86_64-unknown-linux-gnu/release/deps/algos-6abe6ee237edc094) | |
| Benchmarking corner_to_corner_astar | |
| Benchmarking corner_to_corner_astar: Warming up for 3.0000 s | |
| Benchmarking corner_to_corner_astar: Collecting 100 samples in estimated 5.0854 s (177k iterations) | |
| Benchmarking corner_to_corner_astar: Analyzing | |
| corner_to_corner_astar time: [29.258 µs 29.261 µs 29.265 µs] | |
| change: [+92.447% +92.489% +92.532%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 2 (2.00%) high mild | |
| 1 (1.00%) high severe | |
| Benchmarking corner_to_corner_bfs | |
| Benchmarking corner_to_corner_bfs: Warming up for 3.0000 s | |
| Benchmarking corner_to_corner_bfs: Collecting 100 samples in estimated 6.0036 s (15k iterations) | |
| Benchmarking corner_to_corner_bfs: Analyzing | |
| corner_to_corner_bfs time: [400.28 µs 400.94 µs 402.46 µs] | |
| change: [+129.63% +130.34% +131.70%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 11 outliers among 100 measurements (11.00%) | |
| 4 (4.00%) low mild | |
| 5 (5.00%) high mild | |
| 2 (2.00%) high severe | |
| Benchmarking corner_to_corner_dfs | |
| Benchmarking corner_to_corner_dfs: Warming up for 3.0000 s | |
| Benchmarking corner_to_corner_dfs: Collecting 100 samples in estimated 5.2934 s (500 iterations) | |
| Benchmarking corner_to_corner_dfs: Analyzing | |
| corner_to_corner_dfs time: [10.531 ms 10.553 ms 10.585 ms] | |
| change: [+44.350% +46.857% +49.494%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 3 (3.00%) high severe | |
| Benchmarking corner_to_corner_dijkstra | |
| Benchmarking corner_to_corner_dijkstra: Warming up for 3.0000 s | |
| Benchmarking corner_to_corner_dijkstra: Collecting 100 samples in estimated 6.9876 s (10k iterations) | |
| Benchmarking corner_to_corner_dijkstra: Analyzing | |
| corner_to_corner_dijkstra | |
| time: [706.21 µs 706.26 µs 706.31 µs] | |
| change: [+171.31% +171.94% +172.31%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 1 (1.00%) low mild | |
| 2 (2.00%) high severe | |
| Benchmarking corner_to_corner_fringe | |
| Benchmarking corner_to_corner_fringe: Warming up for 3.0000 s | |
| Benchmarking corner_to_corner_fringe: Collecting 100 samples in estimated 5.1911 s (91k iterations) | |
| Benchmarking corner_to_corner_fringe: Analyzing | |
| corner_to_corner_fringe time: [56.934 µs 56.943 µs 56.951 µs] | |
| change: [+189.90% +190.77% +191.42%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 2 outliers among 100 measurements (2.00%) | |
| 1 (1.00%) high mild | |
| 1 (1.00%) high severe | |
| Benchmarking corner_to_corner_idastar | |
| Benchmarking corner_to_corner_idastar: Warming up for 3.0000 s | |
| Benchmarking corner_to_corner_idastar: Collecting 100 samples in estimated 5.0066 s (111k iterations) | |
| Benchmarking corner_to_corner_idastar: Analyzing | |
| Benchmarking corner_to_corner_iddfs | |
| Benchmarking corner_to_corner_iddfs: Warming up for 3.0000 s | |
| corner_to_corner_idastar | |
| time: [44.613 µs 44.702 µs 44.844 µs] | |
| change: [+96.131% +97.887% +99.526%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 9 outliers among 100 measurements (9.00%) | |
| 4 (4.00%) low mild | |
| 2 (2.00%) high mild | |
| 3 (3.00%) high severe | |
| Benchmarking corner_to_corner_iddfs: Collecting 100 samples in estimated 7.4396 s (15k iterations) | |
| Benchmarking corner_to_corner_iddfs: Analyzing | |
| corner_to_corner_iddfs time: [495.45 µs 495.58 µs 495.72 µs] | |
| change: [+18.382% +18.609% +18.742%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Benchmarking no_path_astar | |
| Benchmarking no_path_astar: Warming up for 3.0000 s | |
| Benchmarking no_path_astar: Collecting 100 samples in estimated 7.2675 s (10k iterations) | |
| Benchmarking no_path_astar: Analyzing | |
| no_path_astar time: [742.35 µs 742.51 µs 742.64 µs] | |
| change: [+137.07% +138.30% +138.99%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 1 outliers among 100 measurements (1.00%) | |
| 1 (1.00%) high severe | |
| Benchmarking no_path_bfs | |
| Benchmarking no_path_bfs: Warming up for 3.0000 s | |
| Benchmarking no_path_bfs: Collecting 100 samples in estimated 6.0398 s (15k iterations) | |
| Benchmarking no_path_bfs: Analyzing | |
| no_path_bfs time: [397.35 µs 398.40 µs 399.75 µs] | |
| change: [+144.42% +145.11% +145.97%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 7 outliers among 100 measurements (7.00%) | |
| 1 (1.00%) high mild | |
| 6 (6.00%) high severe | |
| Benchmarking no_path_dijkstra | |
| Benchmarking no_path_dijkstra: Warming up for 3.0000 s | |
| Benchmarking no_path_dijkstra: Collecting 100 samples in estimated 6.9232 s (10k iterations) | |
| Benchmarking no_path_dijkstra: Analyzing | |
| no_path_dijkstra time: [699.12 µs 699.16 µs 699.20 µs] | |
| change: [+163.49% +163.58% +163.66%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 2 outliers among 100 measurements (2.00%) | |
| 1 (1.00%) high mild | |
| 1 (1.00%) high severe | |
| Benchmarking no_path_fringe | |
| Benchmarking no_path_fringe: Warming up for 3.0000 s | |
| Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 5.1s, enable flat sampling, or reduce sample count to 60. | |
| Benchmarking no_path_fringe: Collecting 100 samples in estimated 5.1419 s (5050 iterations) | |
| Benchmarking no_path_fringe: Analyzing | |
| no_path_fringe time: [1.0287 ms 1.0288 ms 1.0290 ms] | |
| change: [+207.11% +207.38% +207.62%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 4 outliers among 100 measurements (4.00%) | |
| 1 (1.00%) high mild | |
| 3 (3.00%) high severe | |
| Benchmarking separate_components | |
| Benchmarking separate_components: Warming up for 3.0000 s | |
| Benchmarking separate_components: Collecting 100 samples in estimated 5.3480 s (10k iterations) | |
| Benchmarking separate_components: Analyzing | |
| separate_components time: [530.88 µs 532.97 µs 535.58 µs] | |
| change: [-72.686% -72.598% -72.495%] (p = 0.00 < 0.05) | |
| Performance has improved. | |
| Found 14 outliers among 100 measurements (14.00%) | |
| 7 (7.00%) low mild | |
| 2 (2.00%) high mild | |
| 5 (5.00%) high severe | |
| Running benches/algos-fill.rs (x86_64-unknown-linux-gnu/release/deps/algos_fill-dacc7246a85b3e12) | |
| Benchmarking fill-corner_to_corner_astar | |
| Benchmarking fill-corner_to_corner_astar: Warming up for 3.0000 s | |
| Benchmarking fill-corner_to_corner_astar: Collecting 100 samples in estimated 5.0412 s (157k iterations) | |
| Benchmarking fill-corner_to_corner_astar: Analyzing | |
| fill-corner_to_corner_astar | |
| time: [33.057 µs 33.066 µs 33.080 µs] | |
| change: [+28.652% +28.703% +28.754%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 5 outliers among 100 measurements (5.00%) | |
| 3 (3.00%) high mild | |
| 2 (2.00%) high severe | |
| Benchmarking fill-corner_to_corner_bfs | |
| Benchmarking fill-corner_to_corner_bfs: Warming up for 3.0000 s | |
| Benchmarking fill-corner_to_corner_bfs: Collecting 100 samples in estimated 5.5101 s (10k iterations) | |
| Benchmarking fill-corner_to_corner_bfs: Analyzing | |
| fill-corner_to_corner_bfs | |
| time: [534.47 µs 534.69 µs 535.02 µs] | |
| change: [+22.053% +22.103% +22.173%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 13 outliers among 100 measurements (13.00%) | |
| 4 (4.00%) low mild | |
| 3 (3.00%) high mild | |
| 6 (6.00%) high severe | |
| Benchmarking fill-corner_to_corner_dfs | |
| Benchmarking fill-corner_to_corner_dfs: Warming up for 3.0000 s | |
| Benchmarking fill-corner_to_corner_dfs: Collecting 100 samples in estimated 5.0631 s (2300 iterations) | |
| Benchmarking fill-corner_to_corner_dfs: Analyzing | |
| fill-corner_to_corner_dfs | |
| time: [2.2007 ms 2.2029 ms 2.2065 ms] | |
| change: [+70.751% +70.941% +71.254%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 8 outliers among 100 measurements (8.00%) | |
| 3 (3.00%) high mild | |
| 5 (5.00%) high severe | |
| Benchmarking fill-corner_to_corner_dijkstra | |
| Benchmarking fill-corner_to_corner_dijkstra: Warming up for 3.0000 s | |
| Benchmarking fill-corner_to_corner_dijkstra: Collecting 100 samples in estimated 5.8312 s (10k iterations) | |
| Benchmarking fill-corner_to_corner_dijkstra: Analyzing | |
| fill-corner_to_corner_dijkstra | |
| time: [620.77 µs 620.82 µs 620.88 µs] | |
| change: [+46.690% +46.754% +46.808%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 5 outliers among 100 measurements (5.00%) | |
| 3 (3.00%) high mild | |
| 2 (2.00%) high severe | |
| Benchmarking fill-corner_to_corner_fringe | |
| Benchmarking fill-corner_to_corner_fringe: Warming up for 3.0000 s | |
| Benchmarking fill-corner_to_corner_fringe: Collecting 100 samples in estimated 5.0309 s (121k iterations) | |
| Benchmarking fill-corner_to_corner_fringe: Analyzing | |
| fill-corner_to_corner_fringe | |
| time: [39.845 µs 39.852 µs 39.862 µs] | |
| change: [+55.766% +55.818% +55.872%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 7 outliers among 100 measurements (7.00%) | |
| 1 (1.00%) low mild | |
| 2 (2.00%) high mild | |
| 4 (4.00%) high severe | |
| Benchmarking fill-corner_to_corner_idastar | |
| Benchmarking fill-corner_to_corner_idastar: Warming up for 3.0000 s | |
| Benchmarking fill-corner_to_corner_idastar: Collecting 100 samples in estimated 5.0484 s (187k iterations) | |
| Benchmarking fill-corner_to_corner_idastar: Analyzing | |
| fill-corner_to_corner_idastar | |
| time: [27.973 µs 27.978 µs 27.983 µs] | |
| change: [+98.656% +98.904% +99.134%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 1 outliers among 100 measurements (1.00%) | |
| 1 (1.00%) high mild | |
| Benchmarking fill-corner_to_corner_iddfs | |
| Benchmarking fill-corner_to_corner_iddfs: Warming up for 3.0000 s | |
| Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 8.4s, enable flat sampling, or reduce sample count to 50. | |
| Benchmarking fill-corner_to_corner_iddfs: Collecting 100 samples in estimated 8.3655 s (5050 iterations) | |
| Benchmarking fill-corner_to_corner_iddfs: Analyzing | |
| fill-corner_to_corner_iddfs | |
| time: [1.6180 ms 1.6183 ms 1.6186 ms] | |
| change: [+64.985% +65.033% +65.089%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 4 outliers among 100 measurements (4.00%) | |
| 1 (1.00%) high mild | |
| 3 (3.00%) high severe | |
| Benchmarking fill-no_path_astar | |
| Benchmarking fill-no_path_astar: Warming up for 3.0000 s | |
| Benchmarking fill-no_path_astar: Collecting 100 samples in estimated 6.1324 s (10k iterations) | |
| Benchmarking fill-no_path_astar: Analyzing | |
| fill-no_path_astar time: [631.74 µs 631.79 µs 631.85 µs] | |
| change: [+42.826% +43.218% +43.473%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 6 outliers among 100 measurements (6.00%) | |
| 1 (1.00%) low mild | |
| 3 (3.00%) high mild | |
| 2 (2.00%) high severe | |
| Benchmarking fill-no_path_bfs | |
| Benchmarking fill-no_path_bfs: Warming up for 3.0000 s | |
| Benchmarking fill-no_path_bfs: Collecting 100 samples in estimated 5.3058 s (10k iterations) | |
| Benchmarking fill-no_path_bfs: Analyzing | |
| fill-no_path_bfs time: [508.69 µs 508.76 µs 508.82 µs] | |
| change: [+23.116% +23.141% +23.169%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 1 outliers among 100 measurements (1.00%) | |
| 1 (1.00%) high severe | |
| Benchmarking fill-no_path_dijkstra | |
| Benchmarking fill-no_path_dijkstra: Warming up for 3.0000 s | |
| Benchmarking fill-no_path_dijkstra: Collecting 100 samples in estimated 5.9159 s (10k iterations) | |
| Benchmarking fill-no_path_dijkstra: Analyzing | |
| fill-no_path_dijkstra time: [621.26 µs 621.46 µs 621.81 µs] | |
| change: [+43.763% +43.807% +43.864%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 10 outliers among 100 measurements (10.00%) | |
| 1 (1.00%) low mild | |
| 7 (7.00%) high mild | |
| 2 (2.00%) high severe | |
| Benchmarking fill-no_path_fringe | |
| Benchmarking fill-no_path_fringe: Warming up for 3.0000 s | |
| Benchmarking fill-no_path_fringe: Collecting 100 samples in estimated 6.9717 s (10k iterations) | |
| Benchmarking fill-no_path_fringe: Analyzing | |
| fill-no_path_fringe time: [652.10 µs 652.16 µs 652.23 µs] | |
| change: [+48.769% +48.804% +48.845%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 6 outliers among 100 measurements (6.00%) | |
| 3 (3.00%) high mild | |
| 3 (3.00%) high severe | |
| Running benches/edmondskarp.rs (x86_64-unknown-linux-gnu/release/deps/edmondskarp-e0723be8f8fe8795) | |
| Benchmarking wikipedia_example_dense | |
| Benchmarking wikipedia_example_dense: Warming up for 3.0000 s | |
| Benchmarking wikipedia_example_dense: Collecting 100 samples in estimated 5.0110 s (838k iterations) | |
| Benchmarking wikipedia_example_dense: Analyzing | |
| wikipedia_example_dense time: [6.0464 µs 6.0479 µs 6.0494 µs] | |
| change: [+109.84% +109.95% +110.08%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 2 outliers among 100 measurements (2.00%) | |
| 1 (1.00%) high mild | |
| 1 (1.00%) high severe | |
| Benchmarking wikipedia_example_sparse | |
| Benchmarking wikipedia_example_sparse: Warming up for 3.0000 s | |
| Benchmarking wikipedia_example_sparse: Collecting 100 samples in estimated 5.0519 s (313k iterations) | |
| Benchmarking wikipedia_example_sparse: Analyzing | |
| wikipedia_example_sparse | |
| time: [16.189 µs 16.191 µs 16.194 µs] | |
| change: [+204.34% +204.45% +204.58%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 7 outliers among 100 measurements (7.00%) | |
| 4 (4.00%) high mild | |
| 3 (3.00%) high severe | |
| Running benches/kuhn_munkres.rs (x86_64-unknown-linux-gnu/release/deps/kuhn_munkres-3f6270c35034b5ff) | |
| Benchmarking Compare kuhn_munkres with different input sizes/32 | |
| Benchmarking Compare kuhn_munkres with different input sizes/32: Warming up for 3.0000 s | |
| Benchmarking Compare kuhn_munkres with different input sizes/32: Collecting 100 samples in estimated 5.0579 s (258k iterations) | |
| Benchmarking Compare kuhn_munkres with different input sizes/32: Analyzing | |
| Compare kuhn_munkres with different input sizes/32 | |
| time: [18.165 µs 18.839 µs 19.533 µs] | |
| change: [+46.259% +52.376% +58.718%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 1 (1.00%) low mild | |
| 2 (2.00%) high mild | |
| Benchmarking Compare kuhn_munkres with different input sizes/64 | |
| Benchmarking Compare kuhn_munkres with different input sizes/64: Warming up for 3.0000 s | |
| Benchmarking Compare kuhn_munkres with different input sizes/64: Collecting 100 samples in estimated 5.3532 s (40k iterations) | |
| Benchmarking Compare kuhn_munkres with different input sizes/64: Analyzing | |
| Compare kuhn_munkres with different input sizes/64 | |
| time: [105.65 µs 110.73 µs 115.83 µs] | |
| change: [+26.167% +33.299% +39.943%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Benchmarking Compare kuhn_munkres with different input sizes/128 | |
| Benchmarking Compare kuhn_munkres with different input sizes/128: Warming up for 3.0000 s | |
| Benchmarking Compare kuhn_munkres with different input sizes/128: Collecting 100 samples in estimated 6.2929 s (10k iterations) | |
| Benchmarking Compare kuhn_munkres with different input sizes/128: Analyzing | |
| Compare kuhn_munkres with different input sizes/128 | |
| time: [621.76 µs 648.49 µs 676.39 µs] | |
| change: [+26.442% +32.554% +39.006%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 1 outliers among 100 measurements (1.00%) | |
| 1 (1.00%) high mild | |
| Benchmarking Compare kuhn_munkres with different input sizes/256 | |
| Benchmarking Compare kuhn_munkres with different input sizes/256: Warming up for 3.0000 s | |
| Benchmarking Compare kuhn_munkres with different input sizes/256: Collecting 100 samples in estimated 5.2095 s (1300 iterations) | |
| Benchmarking Compare kuhn_munkres with different input sizes/256: Analyzing | |
| Compare kuhn_munkres with different input sizes/256 | |
| time: [4.2175 ms 4.3430 ms 4.4746 ms] | |
| change: [+24.054% +29.182% +34.477%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 3 (3.00%) high mild | |
| Benchmarking Compare kuhn_munkres with different input sizes/512 | |
| Benchmarking Compare kuhn_munkres with different input sizes/512: Warming up for 3.0000 s | |
| Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 10.8s, or reduce sample count to 40. | |
| Benchmarking Compare kuhn_munkres with different input sizes/512: Collecting 100 samples in estimated 10.752 s (100 iterations) | |
| Benchmarking Compare kuhn_munkres with different input sizes/512: Analyzing | |
| Compare kuhn_munkres with different input sizes/512 | |
| time: [114.76 ms 115.66 ms 116.57 ms] | |
| change: [+35.059% +36.548% +38.076%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Running benches/movingai.rs (x86_64-unknown-linux-gnu/release/deps/movingai-cb08caf5e0d06d06) | |
| Benchmarking arena | |
| Benchmarking arena: Warming up for 3.0000 s | |
| Benchmarking arena: Collecting 100 samples in estimated 5.9127 s (300 iterations) | |
| Benchmarking arena: Analyzing | |
| arena time: [19.644 ms 19.645 ms 19.647 ms] | |
| change: [+92.368% +92.389% +92.408%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 1 (1.00%) low severe | |
| 1 (1.00%) low mild | |
| 1 (1.00%) high mild | |
| Running benches/separate_components.rs (x86_64-unknown-linux-gnu/release/deps/separate_components-be44c211178c816c) | |
| Benchmarking separate_components | |
| Benchmarking separate_components: Warming up for 3.0000 s | |
| Benchmarking separate_components: Collecting 100 samples in estimated 5.0004 s (2100 iterations) | |
| Benchmarking separate_components: Analyzing | |
| separate_components time: [2.3768 ms 2.3771 ms 2.3774 ms] | |
| change: [+345.39% +346.70% +347.73%] (p = 0.00 < 0.05) | |
| Performance has regressed. | |
| Found 3 outliers among 100 measurements (3.00%) | |
| 2 (2.00%) high mild | |
| 1 (1.00%) high severe |
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