AMD benchmarks have been published. We are seeing a x15.8 speedup with Resnet50
(batch size 32) on AWS's new m5a.24xlarge machine. With a smaller network
(Mobilenet - batch size 32) the speedup is more significant at x38.7. Let's
have a vote to see if the PR to have MKLDNN enabled by default
(https://github.com/apache/incubator-mxnet/pull/12591) can be merged before
1.4.0 release.
On 10/19/18, 9:17 AM, "Pedro Larroy" <pedro.larroy.li...@gmail.com> wrote:
I did pip install mxnet-mkl==1.3.1b20181018 on an AMD Ryzen 1950X and unit
tests are passing.
Is this build using AVX512? in /proc/cpuinfo I see only "avx" flag.
There's no "avx2" like on recent intel cpus.
Pedro.
On Fri, Oct 19, 2018 at 5:12 PM Hagay Lupesko <lupe...@gmail.com> wrote:
> Awesome collaborative effort across many contributors and companies!
>
> The boost is impressive and for MXNet users to get this boost "out of the
> box" is a great benefit and makes MXNet an even better choice.
>
> Alex - can you clarify whether there are any down sides with regards to
> noon AVX-512 architectures, AMD CPUs, etc? Will it gracefully fallback?
>
> Hagay
>
>
> On Fri, Oct 19, 2018, 15:46 Sergio Fernández <wik...@apache.org> wrote:
>
> > If there is no downside on platforms not supporting AVX512 instructions,
> > then +1
> >
> >
> > On Wed, Oct 17, 2018, 14:10 Alex Zai <aza...@gmail.com> wrote:
> >
> > > Hey all,
> > > We have been working hard these past few months to integrate and
> > stabilize
> > > Intel’s MKLDNN deep learning CPU accelerator into Mxnet and have made
> > > incredible progress. On CPUs with AVX512 instructions (such as c5.18x)
> we
> > > have seen performance increase up to 12x and on other platforms (Macs,
> > > AVX2) we seen a speedup of 1.5+. Full list of benchmarks can be found
> > here
> > > (
> > >
> >
> https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=95650764
> > > and https://github.com/apache/incubator-mxnet/pull/12591).
> > >
> > > Currently, using this accelerator requires the developer to either pip
> > > install the mxnet-mkl version of mxnet or to build it themselves from
> > > source. Given that we should try to provide the best performance "out
> of
> > > the box” with mxnet we should include this in the default build. The
> > mkldnn
> > > library is included with in the pip package build so it does not
> require
> > an
> > > external dependency.
> > >
> > > There were concerns that MKLDNN could cause regressions on certain
> > > platforms (as it did with the tensorflow version a while back); but we
> > > added a env flag (MXNET_MKLDNN_ENABLED) that allows users to turn of
> this
> > > feature during runtime. Please bring up any other concerns you may
have
> > and
> > > your thoughts on including this accelerator in the default build.
> > >
> > > Best,
> > > Alex
> > >
> >
>
