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[Caffe2] Add float batch box cox SVE128 implementation #159778
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/159778
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 6b223ae with merge base 01c3c89 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This pull request was exported from Phabricator. Differential Revision: D78994871 |
This pull request was exported from Phabricator. Differential Revision: D78994871 |
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Summary: Pull Request resolved: pytorch#159778 We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
This pull request was exported from Phabricator. Differential Revision: D78994871 |
Summary: Pull Request resolved: pytorch#159778 We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
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This pull request was exported from Phabricator. Differential Revision: D78994871 |
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Summary: Pull Request resolved: pytorch#159778 We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
This pull request was exported from Phabricator. Differential Revision: D78994871 |
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Summary: Pull Request resolved: pytorch#159778 We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
This pull request was exported from Phabricator. Differential Revision: D78994871 |
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Summary: Pull Request resolved: pytorch#159778 We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
This pull request was exported from Phabricator. Differential Revision: D78994871 |
Summary: Pull Request resolved: pytorch#159778 We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
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This pull request was exported from Phabricator. Differential Revision: D78994871 |
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- Please used
auto
to avoid some hard to spot casting errors - Use
C10_LIKELY
/C10_UNLIKELY
instead of__builtin_expect
- Add new unittest or mention in PR which test validates this one
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Summary: We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
Summary: We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
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Summary: We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
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Summary: We are introducing SVE128 perfkernels As first translation, we are implementing float32 batch box cox for SVE128 Test Plan: Sigrid Predictor canary Rollback Plan: Differential Revision: D78994871 Privacy Context Container: L1196524
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@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
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 |
Introduce SVE128 SIMD batch box-cox computation. We've seen about 65% throughput improvement. Privacy Context Container: L1196524 This is a no-op from OSS point of view, therefore it could be landed without tests (see precedence set by pytorch#143627), but we should delete those at some point Pull Request resolved: pytorch#159778 Approved by: https://github.com/malfet
Introduce SVE128 SIMD batch box-cox computation. We've seen about 65% throughput improvement. Privacy Context Container: L1196524 This is a no-op from OSS point of view, therefore it could be landed without tests (see precedence set by pytorch#143627), but we should delete those at some point Pull Request resolved: pytorch#159778 Approved by: https://github.com/malfet
Introduce SVE128 SIMD batch box-cox computation. We've seen about 65% throughput improvement. Privacy Context Container: L1196524 This is a no-op from OSS point of view, therefore it could be landed without tests (see precedence set by pytorch#143627), but we should delete those at some point Pull Request resolved: pytorch#159778 Approved by: https://github.com/malfet
Introduce SVE128 SIMD batch box-cox computation. We've seen about 65% throughput improvement. Privacy Context Container: L1196524 This is a no-op from OSS point of view, therefore it could be landed without tests (see precedence set by pytorch#143627), but we should delete those at some point Pull Request resolved: pytorch#159778 Approved by: https://github.com/malfet
Introduce SVE128 SIMD batch box-cox computation.
We've seen about 65% throughput improvement.
Privacy Context Container: L1196524
This is a no-op from OSS point of view, therefore it could be landed without tests (see precedence set by #143627), but we should delete those at some point
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @jerryzh168 @voznesenskym @penguinwu @EikanWang @Guobing-Chen @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @coconutruben