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From "Zhao, Patric" <patric.z...@intel.com>
Subject RE: MKLDNN Integration Stable Release
Date Wed, 04 Jul 2018 04:24:20 GMT
Thanks, Sandeep,

> * If all existing RNN integration tests pass with MKL-DNN build, this should give
> enough confidence?

This should be the baseline of the merge. We still need to confirm the performance gain from
new API.

> * Also, I remember one of the community member saying "mxnet-mkl" pypi
> package is not compiled with MKLDNN. Not sure about this, but, can we please
> confirm?

After 1.2.0, "*-mkl" is compiled with MKLDNN. But "*-mkl" is not compiled with MKL library
(still using OpenBLAS from pypi).
We are working on this item and try to make both MKL-DNN and MKL library are compiled under
"*-mkl".
 

> -----Original Message-----
> From: sandeep krishnamurthy [mailto:sandeep.krishna98@gmail.com]
> Sent: Wednesday, July 4, 2018 11:27 AM
> To: dev@mxnet.incubator.apache.org
> Subject: Re: MKLDNN Integration Stable Release
> 
> * If all existing RNN integration tests pass with MKL-DNN build, this should give
> enough confidence?
> * Also, I remember one of the community member saying "mxnet-mkl" pypi
> package is not compiled with MKLDNN. Not sure about this, but, can we please
> confirm?
> 
> Best,
> Sandeep
> 
> On Tue, Jul 3, 2018 at 7:37 PM Zhao, Patric <patric.zhao@intel.com> wrote:
> 
> > Hi Alex,
> >
> > Regarding RNN, the first version of MKL-DNN RNN API is available in
> > the MKL-DNN master branch.
> > We have integrated it in our local branch and you can try our code
> > (still in developments).
> >
> >
> > https://github.com/lihaofd/incubator-mxnet/blob/mkldnn-rnn/src/operato
> > r/nn/mkldnn/mkldnn_rnn_impl.h
> >
> > We plan to PR our integration into MXNET master when both
> > functionality and performance are qualified.
> >
> > Thanks,
> >
> > --Patric
> >
> > > -----Original Message-----
> > > From: Alex Zai [mailto:azai91@gmail.com]
> > > Sent: Wednesday, July 4, 2018 1:17 AM
> > > To: dev@mxnet.incubator.apache.org
> > > Subject: MKLDNN Integration Stable Release
> > >
> > > We are preparing a stable release of MKL-DNN integration in 1.3.0
> > > (experimental since 1.2.0), which supports acceleration of
> > > operations
> > such as
> > > Convolution, Deconvolution, FullyConnected, Pooling, Batch
> > > Normalization, Activation, LRN, Softmax. Currently the RNN operator
> > > is not supported as
> > the
> > > MKL-DNN API is still experimental; however, they hope to release a
> > > more stable version RNN API this or next week in MKL-DNN 0.15.
> > >
> > > We will have CPP unit test support on these operators and I am
> > > planning
> > to
> > > write python unit tests to compare a RNN network's results from the
> > MKLDNN
> > > backend with that of the GPU to test accuracy. Is there any
> > > additional
> > coverage
> > > that you think we should cover in the next two weeks?
> > >
> > > Alex
> >
> 
> 
> --
> Sandeep Krishnamurthy
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