[Profiler] Switch to thread local subqueues to reduce lock contention. #74151
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pytorch#74151) Summary: Pull Request resolved: pytorch#74151 The first of several changes to move to an optimized recording data structure to back profiler. This PR keeps the existing monolithic `OpEventData` struct, but splits storage into thread local subqueues so we don't have to lock to insert. Test Plan: Unit tests and benchmarks. The single threaded benchmark is unchanged, and the multithreaded stress test dropped from ~21 us to ~6us. Reviewed By: chaekit Differential Revision: D34720171 fbshipit-source-id: e68589551ff4b05afef4d4040c0e64b2f21e7c27
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#74151) Summary: Pull Request resolved: #74151 The first of several changes to move to an optimized recording data structure to back profiler. This PR keeps the existing monolithic `OpEventData` struct, but splits storage into thread local subqueues so we don't have to lock to insert. Test Plan: Unit tests and benchmarks. The single threaded benchmark is unchanged, and the multithreaded stress test dropped from ~21 us to ~6us. Reviewed By: chaekit Differential Revision: D34720171 fbshipit-source-id: 90b5ebe618b91099e0a19c1f31cfcd8fe1c2ea12
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Summary: The first of several changes to move to an optimized recording data structure to back profiler. This PR keeps the existing monolithic
OpEventDatastruct, but splits storage into thread local subqueues so we don't have to lock to insert.Test Plan: Unit tests and benchmarks. The single threaded benchmark is unchanged, and the multithreaded stress test dropped from ~21 us to ~6us.
Reviewed By: chaekit
Differential Revision: D34720171