[DPER] Introduce barrier operation to force synchronization of threads in async execution#49322
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kennyhorror wants to merge 1 commit intopytorch:masterfrom
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[DPER] Introduce barrier operation to force synchronization of threads in async execution#49322kennyhorror wants to merge 1 commit intopytorch:masterfrom
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…s in async execution (pytorch#49322) Summary: Pull Request resolved: pytorch#49322 In some cases async execution might loose dependencies (Alias like ops) or produce suboptimal scheduling when there is an option which parts to schedule first. Example of the later behavior can happen in ModelParallel training where copy can get lower priority compared to the rest of the execution on the given GPU, which will caused other GPUs to starve. This operator allows to address these issues by introducing extra explicit dependencies between ops. Test Plan: Unit-test/ E2E testing in the future diffs. Reviewed By: xianjiec Differential Revision: D24933471 fbshipit-source-id: 18e29c0899a97183115339528dc5c3c8b090205a
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This pull request was exported from Phabricator. Differential Revision: D24933471 |
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Codecov Report
@@ Coverage Diff @@
## master #49322 +/- ##
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Coverage 80.56% 80.56%
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Files 1875 1875
Lines 202701 202701
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+ Hits 163307 163309 +2
+ Misses 39394 39392 -2 |
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This pull request has been merged in 46debe7. |
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…s in async execution (pytorch#49322) Summary: Pull Request resolved: pytorch#49322 In some cases async execution might loose dependencies (Alias like ops) or produce suboptimal scheduling when there is an option which parts to schedule first. Example of the later behavior can happen in ModelParallel training where copy can get lower priority compared to the rest of the execution on the given GPU, which will caused other GPUs to starve. This operator allows to address these issues by introducing extra explicit dependencies between ops. Test Plan: Unit-test/ E2E testing in the future diffs. Reviewed By: xianjiec Differential Revision: D24933471 fbshipit-source-id: 1668994c7856d73926cde022378a99e1e8db3567
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Summary:
In some cases async execution might loose dependencies (Alias like ops) or produce suboptimal scheduling when there is an option which parts to schedule first. Example of the later behavior can happen in ModelParallel training where copy can get lower priority compared to the rest of the execution on the given GPU, which will caused other GPUs to starve.
This operator allows to address these issues by introducing extra explicit dependencies between ops.
Test Plan:
Unit-test/
E2E testing in the future diffs.
Reviewed By: xianjiec
Differential Revision: D24933471