**Benchmark data** The benchmark data contains data collected on Linux and Mac, and compared between build with and w.o. MKLDNN, as the computation on a build w.o. MKLDNN is too slow, only the performance data selected CNN models are listed, benchmarking script based on example\image-classfication\benchmark_score.py.
**On MacOS,** the default compilation configurations disabling the OPENMP, below tables listing the perf datas on build with MKLDNN(OPENMP enabled), and the build without MKLDNN. **_(HW is iMac Pro with 8-core Xeon-W)_** VGG16 batch size | MKLDNN-enabled | w.o. MKLDNN | boost-up -- | -- | -- | -- 1 | 20.913986 | 7.821254 | 267.40% 16 | 24.273071 | 8.438211 | 287.66% 32 | 24.704907 | 8.480799 | 291.30% 64 | 24.94608 | 8.524874 | 292.63% 128 | 25.074148 | 8.53283 | 293.86% 256 | 25.2629 | 8.535707 | 295.97% Inception-v3 batch size | MKLDNN-enabled | w.o. MKLDNN | boost-up -- | -- | -- | -- 1 | 41.431404 | 10.323434 | 401.33% 16 | 54.312317 | 10.665803 | 509.22% 32 | 54.604119 | 10.621378 | 514.10% 64 | 54.39568 | 10.605843 | 512.88% 128 | 54.410785 | 10.62466 | 512.12% 256 | 54.614424 | 10.616772 | 514.42% Inception-V4 batch size | MKLDNN-enabled | w.o. MKLDNN | boost-up -- | -- | -- | -- 1 | 20.715221 | 5.655873 | 366.26% 16 | 26.249734 | 5.779357 | 454.20% 32 | 26.197659 | 5.761883 | 454.67% 64 | 26.16153 | 5.771389 | 453.30% 128 | 26.247461 | 5.778834 | 454.20% 256 | 26.313875 | 5.77839 | 455.38% ResNet-50 batch size | MKLDNN-enabled | w.o. MKLDNN | boost-up -- | -- | -- | -- 1 | 41.70109 | 19.246681 | 216.67% 16 | 43.132788 | 20.854712 | 206.83% 32 | 41.613291 | 20.570733 | 202.29% 64 | 38.13329 | 20.652445 | 184.64% 128 | 38.839577 | 20.685878 | 187.76% 256 | 38.853521 | 20.68953 | 187.79% MobileNet batch size | MKLDNN-enabled | w.o. MKLDNN | boost-up -- | -- | -- | -- 1 | 200.91608 | 36.047475 | 557.37% 16 | 287.614019 | 37.224849 | 772.64% 32 | 277.838051 | 36.914548 | 752.65% 64 | 274.474078 | 36.939298 | 743.04% 128 | 273.622323 | 37.04172 | 738.69% 256 | 273.445636 | 36.947783 | 740.09% [ Full content available at: https://github.com/apache/incubator-mxnet/pull/12591 ] This message was relayed via gitbox.apache.org for [email protected]
