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 > > > > > >