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@robieta robieta commented Feb 25, 2022

Summary: We can do better than vector or deque, and it's sufficiently important to the hot path to justify a custom container. (This is part of the larger queue refactor, but this is a standalone drop-in replacement so we don't need to wait.)

Test Plan: It's a pretty simple container type, so I just added a few cpp tests for emplace and read back. I also ran the overhead benchmark (replicates=9) with both --stressTestKineto (0.99 -> 0.94 us) and --stressTestKineto --kinetoProfileMemory (1.36 -> 1.27 us).

Differential Revision: D34231072

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This pull request was exported from Phabricator. Differential Revision: D34231072

@albanD albanD removed their request for review February 28, 2022 16:18
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This pull request was exported from Phabricator. Differential Revision: D34231072

@robieta robieta force-pushed the export-D34231072 branch from 5d755d4 to 8fcf1d0 Compare March 6, 2022 19:59
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This pull request was exported from Phabricator. Differential Revision: D34231072

@robieta robieta force-pushed the export-D34231072 branch from 8fcf1d0 to fda6ee7 Compare March 7, 2022 17:02
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This pull request was exported from Phabricator. Differential Revision: D34231072

@robieta robieta force-pushed the export-D34231072 branch from fda6ee7 to f2a2d9f Compare March 8, 2022 17:06
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This pull request was exported from Phabricator. Differential Revision: D34231072

Summary:
Pull Request resolved: pytorch#73409

We can do better than `vector` or `deque`, and it's sufficiently important to the hot path to justify a custom container. (This is part of the larger queue refactor, but this is a standalone drop-in replacement so we don't need to wait.)

Test Plan: It's a pretty simple container type, so I just added a few cpp tests for emplace and read back. I also ran the overhead benchmark (replicates=9) with both `--stressTestKineto` (0.99 -> 0.94 us) and `--stressTestKineto --kinetoProfileMemory` (1.36 -> 1.27 us).

Reviewed By: swolchok

Differential Revision: D34231072

fbshipit-source-id: fccbc9ab7adaa1645c631fee6aa85787f85df599
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This pull request was exported from Phabricator. Differential Revision: D34231072

facebook-github-bot pushed a commit that referenced this pull request Mar 11, 2022
Summary:
Pull Request resolved: #73409

We can do better than `vector` or `deque`, and it's sufficiently important to the hot path to justify a custom container. (This is part of the larger queue refactor, but this is a standalone drop-in replacement so we don't need to wait.)

Test Plan: It's a pretty simple container type, so I just added a few cpp tests for emplace and read back. I also ran the overhead benchmark (replicates=9) with both `--stressTestKineto` (0.99 -> 0.94 us) and `--stressTestKineto --kinetoProfileMemory` (1.36 -> 1.27 us).

Reviewed By: swolchok

Differential Revision: D34231072

fbshipit-source-id: ed57299729d444d59cf843a0d38a3ee2240eeec1
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Hey @robieta.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.

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