[inductor] modify the heuristic for loop split optimization #137550
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/137550
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (3 Unrelated Failures)As of commit 0cd0434 with merge base d0fd42e ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
BROKEN TRUNK - The following jobs failed but was present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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ghstack-source-id: 21156f1 Pull Request resolved: pytorch#137550
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topic: not user facing
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Yes, this PR will bring about 20% performance improvements for two torchbench models(functorch_dp_cifar10, opacus_cifar10) and one timm model(sebotnet33ts_256). |
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Dec 2, 2024
…137550) ### Summary 1. Improve the heuristic for loop split optimization: The divisor needs to be an integer and cannot be too small (needs to be greater than 8, this threshold has been tuned). 2. Improve the heuristic for disabling vectorization: add quantity_threshold and relax ratio_threshold for the number of non-contiguous load/store/index_expr in the loop body. This PR will bring performance improvements for two torchbench models(functorch_dp_cifar10, opacus_cifar10) and one timm model(sebotnet33ts_256). Pull Request resolved: pytorch#137550 Approved by: https://github.com/leslie-fang-intel, https://github.com/jgong5, https://github.com/jansel
pobin6
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Dec 5, 2024
…137550) ### Summary 1. Improve the heuristic for loop split optimization: The divisor needs to be an integer and cannot be too small (needs to be greater than 8, this threshold has been tuned). 2. Improve the heuristic for disabling vectorization: add quantity_threshold and relax ratio_threshold for the number of non-contiguous load/store/index_expr in the loop body. This PR will bring performance improvements for two torchbench models(functorch_dp_cifar10, opacus_cifar10) and one timm model(sebotnet33ts_256). Pull Request resolved: pytorch#137550 Approved by: https://github.com/leslie-fang-intel, https://github.com/jgong5, https://github.com/jansel
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Stack from ghstack (oldest at bottom):
Summary
This PR will bring performance improvements for two torchbench models(functorch_dp_cifar10, opacus_cifar10) and one timm model(sebotnet33ts_256).
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov