[cuda] Limit grid size for torch.cat kernel on aligned16 contig tensors#103233
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valentinandrei wants to merge 1 commit intopytorch:mainfrom
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[cuda] Limit grid size for torch.cat kernel on aligned16 contig tensors#103233valentinandrei wants to merge 1 commit intopytorch:mainfrom
valentinandrei wants to merge 1 commit intopytorch:mainfrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/103233
Note: Links to docs will display an error until the docs builds have been completed. ✅ 1 Unrelated FailureAs of commit dcac7e1: UNSTABLE - The following job failed but was likely due to flakiness present on trunk and has been marked as unstable:
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Jun 8, 2023
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@pytorchbot merge -ic |
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@pytorchbot merge -i |
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Merge startedYour change will be merged while ignoring the following 1 checks: pull / linux-focal-py3.8-gcc7 / test (distributed, 1, 2, linux.2xlarge, unstable) Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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When torch.cat gets called on a list of contiguous tensors that are aligned on a 16B boundary in memory, the number of thread blocks used is directly proportional with the maximum size of the tensors in the list. If one or more tensors are very large while the others are small, a high number of thread blocks results in useless redundant loads of the input metadata. This PR limits the grid size and improves the performance of cat when used on list of tensors with large variations in size.
Used the same test program from #102815 but added new cases with list of tensors with varying sizes.