[cuda] introduce trace tracker callback in cache allocator #112238
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/112238
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (4 Unrelated Failures)As of commit f289e51 with merge base 9d09d29 ( UNSTABLE - The following jobs failed but were likely due to flakiness present on trunk and has been marked as unstable:
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This looks good, I only have minor comments. It will need some test from within PyTorch to make sure the events get called.
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Addressed comments and added a unit test |
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@pytorchbot label "topic: not user facing" |
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Looks good! Thanks for getting that test to run
…pytorch#112238) Summary: This patch prototypes a trace tracker callback mechanism based on existing TraceEntry records. - It allows external of cache allocator to "attach" trace tracker callbacks. - When a TraceEntry is recorded, it triggers all attached callbacks. Callbacks can selectively behave based on the trace action. - **RISK**: The attached callback would be called within an allocator call stack (e.g., free during an allocate call). Potential deadlock may occur if other locks are called within the callback and has interdependency w/ the device allocator lock. It is the callback developer's responsibility to avoid any potential deadlock. - **ADVICE**: The callback mechanism is designed **only for Pytorch internal use**. We should not expose it to Python layer due to Python GIL that would cause a deadlock. See example in D50726970 that attaches NCCL register/deregister hooks via the trace tracker callback, so that all CUDA segments allocated by the allocator can be registered to NCCL communicators before any NCCL communication happens. This enables fast zero copy algorithms in NCCL. Reviewed By: zdevito Differential Revision: D50726971
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@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
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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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…12238) Summary: This patch prototypes a trace tracker callback mechanism based on existing TraceEntry records. - It allows external of cache allocator to "attach" trace tracker callbacks. - When a TraceEntry is recorded, it triggers all attached callbacks. Callbacks can selectively behave based on the trace action. - **RISK**: The attached callback would be called within an allocator call stack (e.g., free during an allocate call). Potential deadlock may occur if other locks are called within the callback and has interdependency w/ the device allocator lock. It is the callback developer's responsibility to avoid any potential deadlock. - **ADVICE**: The callback mechanism is designed **only for Pytorch internal use**. We should not expose it to Python layer due to Python GIL that would cause a deadlock. See example in D50726970 that attaches NCCL register/deregister hooks via the trace tracker callback, so that all CUDA segments allocated by the allocator can be registered to NCCL communicators before any NCCL communication happens. This enables fast zero copy algorithms in NCCL. Differential Revision: D50726971 Pull Request resolved: pytorch#112238 Approved by: https://github.com/zdevito
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…12238) Summary: This patch prototypes a trace tracker callback mechanism based on existing TraceEntry records. - It allows external of cache allocator to "attach" trace tracker callbacks. - When a TraceEntry is recorded, it triggers all attached callbacks. Callbacks can selectively behave based on the trace action. - **RISK**: The attached callback would be called within an allocator call stack (e.g., free during an allocate call). Potential deadlock may occur if other locks are called within the callback and has interdependency w/ the device allocator lock. It is the callback developer's responsibility to avoid any potential deadlock. - **ADVICE**: The callback mechanism is designed **only for Pytorch internal use**. We should not expose it to Python layer due to Python GIL that would cause a deadlock. See example in D50726970 that attaches NCCL register/deregister hooks via the trace tracker callback, so that all CUDA segments allocated by the allocator can be registered to NCCL communicators before any NCCL communication happens. This enables fast zero copy algorithms in NCCL. Differential Revision: D50726971 Pull Request resolved: pytorch#112238 Approved by: https://github.com/zdevito
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Summary:
This patch prototypes a trace tracker callback mechanism based on existing TraceEntry records.
See example in D50726970 that attaches NCCL register/deregister hooks via the trace tracker callback, so that all CUDA segments allocated by the allocator can be registered to NCCL communicators before any NCCL communication happens. This enables fast zero copy algorithms in NCCL.
Differential Revision: D50726971