Cascadelake MKL-DNN

2 x Intel Xeon Platinum 8280 testing with a GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS) and ASPEED Family on Ubuntu 18.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/1904193-HV-CASCADELA65.

Cascadelake MKL-DNNProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverCompilerFile-SystemScreen Resolution2 x 82802 x Intel Xeon Platinum 8280 @ 4.00GHz (56 Cores / 112 Threads)GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS)Intel Sky Lake-E DMI3 Registers386048MBSamsung SSD 970 PRO 512GBASPEED FamilyVE2282 x Intel X722 for 1GbE + 2 x QLogic FastLinQ QL41000 10/25/40/50GbEUbuntu 18.045.1.0-999-generic (x86_64) 20190416GNOME Shell 3.28.3X Server 1.20.1modesetting 1.20.1GCC 7.3.0ext41920x1080OpenBenchmarking.org- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v - Scaling Governor: intel_pstate powersave- __user pointer sanitization + Enhanced IBRS IBPB: conditional RSB filling + SSB disabled via prctl and seccomp

Cascadelake MKL-DNNmkl-dnn: IP Batch 1D - f32mkl-dnn: IP Batch All - f32mkl-dnn: IP Batch 1D - u8s8u8s32mkl-dnn: IP Batch 1D - u8s8f32s32mkl-dnn: IP Batch All - u8s8u8s32mkl-dnn: IP Batch All - u8s8f32s32mkl-dnn: Convolution Batch conv_3d - f32mkl-dnn: Convolution Batch conv_all - f32mkl-dnn: Deconvolution Batch deconv_1d - f32mkl-dnn: Deconvolution Batch deconv_3d - f32mkl-dnn: Convolution Batch conv_alexnet - f32mkl-dnn: Deconvolution Batch deconv_all - f32mkl-dnn: Convolution Batch conv_3d - u8s8u8s32mkl-dnn: Convolution Batch conv_3d - u8s8f32s32mkl-dnn: Convolution Batch conv_all - u8s8u8s32mkl-dnn: Convolution Batch conv_all - u8s8f32s32mkl-dnn: Convolution Batch conv_googlenet_v3 - f32mkl-dnn: Deconvolution Batch deconv_1d - u8s8u8s32mkl-dnn: Deconvolution Batch deconv_3d - u8s8u8s32mkl-dnn: Convolution Batch conv_alexnet - u8s8u8s32mkl-dnn: Deconvolution Batch deconv_1d - u8s8f32s32mkl-dnn: Deconvolution Batch deconv_3d - u8s8f32s32mkl-dnn: Deconvolution Batch deconv_all - u8s8u8s32mkl-dnn: Convolution Batch conv_alexnet - u8s8f32s32mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8u8s32mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8f32s322 x 828011.65101.173.543.6320.4520.383.293820.951.1048.429842607.672633.7112601300.7121.130.232256.1914.060.232181.053982.3519.245.716.16OpenBenchmarking.org

MKL-DNN

Harness: IP Batch 1D - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: IP Batch 1D - Data Type: f322 x 82803691215SE +/- 0.17, N = 311.65MIN: 6.621. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: IP Batch All - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: IP Batch All - Data Type: f322 x 828020406080100SE +/- 0.52, N = 3101.17MIN: 59.171. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: IP Batch 1D - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: IP Batch 1D - Data Type: u8s8u8s322 x 82800.79651.5932.38953.1863.9825SE +/- 0.04, N = 83.54MIN: 2.161. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: IP Batch 1D - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: IP Batch 1D - Data Type: u8s8f32s322 x 82800.81681.63362.45043.26724.084SE +/- 0.04, N = 73.63MIN: 2.281. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: IP Batch All - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: IP Batch All - Data Type: u8s8u8s322 x 8280510152025SE +/- 0.04, N = 320.45MIN: 13.031. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: IP Batch All - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: IP Batch All - Data Type: u8s8f32s322 x 8280510152025SE +/- 0.28, N = 320.38MIN: 13.211. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_3d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_3d - Data Type: f322 x 82800.74031.48062.22092.96123.7015SE +/- 0.01, N = 33.29MIN: 3.151. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_all - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_all - Data Type: f322 x 828080160240320400SE +/- 0.51, N = 3382MIN: 375.611. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_1d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_1d - Data Type: f322 x 82800.21380.42760.64140.85521.069SE +/- 0.00, N = 30.95MIN: 0.911. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_3d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_3d - Data Type: f322 x 82800.24750.4950.74250.991.2375SE +/- 0.01, N = 31.10MIN: 1.061. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_alexnet - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_alexnet - Data Type: f322 x 82801122334455SE +/- 0.07, N = 348.42MIN: 47.51. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_all - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_all - Data Type: f322 x 82802004006008001000SE +/- 9.53, N = 3984MIN: 921.291. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_3d - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_3d - Data Type: u8s8u8s322 x 82806001200180024003000SE +/- 0.25, N = 32607.67MIN: 2602.211. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_3d - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_3d - Data Type: u8s8f32s322 x 82806001200180024003000SE +/- 2.40, N = 32633.71MIN: 2625.771. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_all - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_all - Data Type: u8s8u8s322 x 828030060090012001500SE +/- 1.87, N = 31260MIN: 1253.931. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_all - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_all - Data Type: u8s8f32s322 x 828030060090012001500SE +/- 2.20, N = 31300.71MIN: 1292.311. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_googlenet_v3 - Data Type: f322 x 8280510152025SE +/- 0.05, N = 321.13MIN: 20.671. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_1d - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_1d - Data Type: u8s8u8s322 x 82800.05180.10360.15540.20720.259SE +/- 0.00, N = 30.23MIN: 0.211. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_3d - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_3d - Data Type: u8s8u8s322 x 82805001000150020002500SE +/- 1.11, N = 32256.19MIN: 2251.871. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_alexnet - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_alexnet - Data Type: u8s8u8s322 x 828048121620SE +/- 0.00, N = 314.06MIN: 13.81. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32s322 x 82800.05180.10360.15540.20720.259SE +/- 0.00, N = 30.23MIN: 0.211. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32s322 x 82805001000150020002500SE +/- 2.64, N = 32181.05MIN: 2170.151. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Deconvolution Batch deconv_all - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Deconvolution Batch deconv_all - Data Type: u8s8u8s322 x 82809001800270036004500SE +/- 6.44, N = 33982.35MIN: 3926.331. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32s322 x 8280510152025SE +/- 0.05, N = 319.24MIN: 18.451. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8u8s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8u8s322 x 82801.28482.56963.85445.13926.424SE +/- 0.01, N = 35.71MIN: 5.521. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

MKL-DNN

Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32s32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN 2019-04-16Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32s322 x 8280246810SE +/- 0.02, N = 36.16MIN: 5.891. (CXX) g++ options: -std=c++11 -march=native -mtune=native -fPIC -fopenmp -O3 -pie -lmklml_intel -ldl

Phoronix Test Suite v10.8.4