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 >
