[inductor] pack linear for FP32 dynamic mode #157542
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/157542
Note: Links to docs will display an error until the docs builds have been completed. ⏳ No Failures, 1 PendingAs of commit 0ccd7e7 with merge base 3008d98 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
CaoE
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jansel
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Summary: Currently, Linear in FP32 dynamic mode(batch_size has free symbols) does not support weight prepacking since MKL Linear does not support dynamic mode. This PR uses oneDNN Linear to support Linear weight prepacking in FP32 dynamic mode. I tested the Inductor benchmark in FP32 dynamic mode on CPU using this PR, and saw ~8% improvement in timm_models geomean speedup, ~2% improvement in torchbench geomean speedup, and no change in huggingface. There are about 18 models with different degrees of performance improvement, among which BERT_pytorch, soft_actor_critic, BlenderbotForCausalLM, ElectraForCausalLM, crossvit_9_240, mobilevit_s, twins_pcpvt_base have more than 20% performance improvement. X-link: pytorch/pytorch#157542 Approved by: https://github.com/CaoE, https://github.com/jansel Reviewed By: seemethere Differential Revision: D80465691 fbshipit-source-id: 1a3627884c3769f292eec4c3ad396e7c91162c46
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Summary: Currently, Linear in FP32 dynamic mode(batch_size has free symbols) does not support weight prepacking since MKL Linear does not support dynamic mode. This PR uses oneDNN Linear to support Linear weight prepacking in FP32 dynamic mode. I tested the Inductor benchmark in FP32 dynamic mode on CPU using this PR, and saw ~8% improvement in timm_models geomean speedup, ~2% improvement in torchbench geomean speedup, and no change in huggingface. There are about 18 models with different degrees of performance improvement, among which BERT_pytorch, soft_actor_critic, BlenderbotForCausalLM, ElectraForCausalLM, crossvit_9_240, mobilevit_s, twins_pcpvt_base have more than 20% performance improvement. Pull Request resolved: pytorch#157542 Approved by: https://github.com/CaoE, https://github.com/jansel
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Stack from ghstack (oldest at bottom):
Summary:
Currently, Linear in FP32 dynamic mode(batch_size has free symbols) does not support weight prepacking since MKL Linear does not support dynamic mode. This PR uses oneDNN Linear to support Linear weight prepacking in FP32 dynamic mode.
I tested the Inductor benchmark in FP32 dynamic mode on CPU using this PR, and saw ~8% improvement in timm_models geomean speedup, ~2% improvement in torchbench geomean speedup, and no change in huggingface. There are about 18 models with different degrees of performance improvement, among which BERT_pytorch, soft_actor_critic, BlenderbotForCausalLM, ElectraForCausalLM, crossvit_9_240, mobilevit_s, twins_pcpvt_base have more than 20% performance improvement.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @coconutruben @Lucaskabela @mlazos