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Open avoskoboinyk-lohika opened this issue 2 years ago • 11 comments

Details:

Cache twiddles for FFT function and add x86 JIT implementations.

ID: 62580

It depends on https://github.com/openvinotoolkit/oneDNN/pull/142

avoskoboinyk-lohika avatar Jun 22 '22 06:06 avoskoboinyk-lohika

@liubo-intel Could you please take a review?

yuxu42 avatar Jun 29 '22 08:06 yuxu42

@chenhu-wang @xuchen-intel @usstq please help review this PR. Thanks.

ceciliapeng2011 avatar Jun 29 '22 08:06 ceciliapeng2011

Please refer to https://github.com/openvinotoolkit/openvino/blob/master/src/tests/functional/plugin/cpu/single_layer_tests/matmul.cpp and add CPUSpecificParams unit tests to cover all different executor branches. Thanks.

ceciliapeng2011 avatar Jul 13 '22 08:07 ceciliapeng2011

@dmitry-gorokhov anyone from Russia team could have a look at this PR?

ceciliapeng2011 avatar Jul 20 '22 01:07 ceciliapeng2011

@nshchego Please review the PR

dmitry-gorokhov avatar Jul 20 '22 09:07 dmitry-gorokhov

ache twiddles for FFT function and add x86 JIT implementations.

Please add the ticket number.

nshchego avatar Jul 20 '22 12:07 nshchego

@nshchego Any additional comments from your side?

dmitry-gorokhov avatar Aug 29 '22 06:08 dmitry-gorokhov

Is there a PR for oneDNN changes?

nshchego avatar Sep 06 '22 05:09 nshchego

Yes, it's located here: https://github.com/openvinotoolkit/oneDNN/pull/142

avoskoboinyk-lohika avatar Sep 06 '22 12:09 avoskoboinyk-lohika

The code LGTM. We need to run Bench to prove the performance gain. I'll try to do it soon.

nshchego avatar Sep 13 '22 08:09 nshchego

@avoskoboinyk-lohika Could you please add a link to oneDNN PR to the description

EgorDuplensky avatar Sep 15 '22 10:09 EgorDuplensky

The code LGTM. We need to run Bench to prove the performance gain. I'll try to do it soon.

Did you have a chance to check the performance?

maxnick avatar Sep 26 '22 08:09 maxnick

@ceciliapeng2011, do we have enough data on performance validation to merge the PR?

maxnick avatar Nov 02 '22 11:11 maxnick