[ML] Allow on-the-fly adjustment of the number of threads in use#2232
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tveasey merged 6 commits intoelastic:mainfrom Mar 18, 2022
Merged
[ML] Allow on-the-fly adjustment of the number of threads in use#2232tveasey merged 6 commits intoelastic:mainfrom
tveasey merged 6 commits intoelastic:mainfrom
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droberts195
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Mar 17, 2022
edsavage
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Allows overriding the PR number from the command line, useful for local testing of the GitHub comment feature without being in a Buildkite PR build environment. Tested end-to-end against build elastic#2232 (Bayesian test timeout), posting to a throwaway PR. Both initial post and update-in-place (deduplication) verified working. Made-with: Cursor
edsavage
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Mar 20, 2026
Allows overriding the PR number from the command line, useful for local testing of the GitHub comment feature without being in a Buildkite PR build environment. Tested end-to-end against build elastic#2232 (Bayesian test timeout), posting to a throwaway PR. Both initial post and update-in-place (deduplication) verified working. Made-with: Cursor
edsavage
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Mar 24, 2026
Allows overriding the PR number from the command line, useful for local testing of the GitHub comment feature without being in a Buildkite PR build environment. Tested end-to-end against build elastic#2232 (Bayesian test timeout), posting to a throwaway PR. Both initial post and update-in-place (deduplication) verified working. Made-with: Cursor
edsavage
added a commit
to edsavage/ml-cpp
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Mar 26, 2026
Allows overriding the PR number from the command line, useful for local testing of the GitHub comment feature without being in a Buildkite PR build environment. Tested end-to-end against build elastic#2232 (Bayesian test timeout), posting to a throwaway PR. Both initial post and update-in-place (deduplication) verified working. Made-with: Cursor
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For PyTorch model inference we want to be able to control the number of threads we assign to parallel calls to forward on-the-fly to adjust the number of cores each model consumes on a node as cluster wide tasks are added or removed. This lays the groundwork by adding a dynamic setting for the number of threads the pool will use. The idea is we always start the process thread pool with the hardware concurrency (divided by the number of threads we give libtorch), but then adjust the threads actually used by control message. Unused threads will simply be idle waiting to pop an empty queue so are effectively free.
cc @dimitris-athanasiou.