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[CPU] Refactor CPU W8A8 scaled_mm #23071
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Code Review
This pull request is a significant and well-executed refactoring of the CPU W8A8 scaled_mm implementation. The introduction of oneDNN with pre-packed weights and cached primitives is a great step towards improving performance, as demonstrated by the benchmark results. The new CPUScaledMMLinearKernel and the handler-based approach provide a much cleaner and more efficient architecture. The code is well-structured and the addition of comprehensive tests is commendable. I've identified one critical issue regarding tensor memory layout that could lead to runtime errors, which I've detailed in a specific comment.
Signed-off-by: jiang1.li <jiang1.li@intel.com>
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Signed-off-by: jiang1.li <jiang1.li@intel.com> Signed-off-by: Duncan Moss <djm.moss@gmail.com>
Signed-off-by: jiang1.li <jiang1.li@intel.com>
Signed-off-by: jiang1.li <jiang1.li@intel.com> Signed-off-by: Xiao Yu <xiao.yu@amd.com>
Signed-off-by: jiang1.li <jiang1.li@intel.com>
Signed-off-by: jiang1.li <jiang1.li@intel.com>
Signed-off-by: jiang1.li <jiang1.li@intel.com>
Signed-off-by: jiang1.li <jiang1.li@intel.com>
Purpose
Refactor CPU W8A8 scaled_mm to:
cc @Akashcodes732 @nishith-fujitsu It will be better if you can verify this on POWER and ARM, thanks!
this
main
Test Plan
unit tests
Test Result
Pass
(Optional) Documentation Update
Essential Elements of an Effective PR Description Checklist
supported_models.mdandexamplesfor a new model.