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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 1904193-HV-CASCADELA65
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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
2 x 8280
April 19 2019
  3 Hours
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Cascadelake MKL-DNNOpenBenchmarking.orgPhoronix Test Suite2 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 7.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverCompilerFile-SystemScreen ResolutionCascadelake MKL-DNN BenchmarksSystem Logs- --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: Convolution Batch conv_all - u8s8u8s32mkl-dnn: Convolution Batch conv_all - u8s8f32s32mkl-dnn: Convolution Batch conv_all - f32mkl-dnn: Deconvolution Batch deconv_all - u8s8u8s32mkl-dnn: Deconvolution Batch deconv_all - f32mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8u8s32mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8f32s32mkl-dnn: Convolution Batch conv_googlenet_v3 - f32mkl-dnn: IP Batch All - f32mkl-dnn: IP Batch All - u8s8f32s32mkl-dnn: IP Batch All - u8s8u8s32mkl-dnn: Convolution Batch conv_3d - u8s8u8s32mkl-dnn: Convolution Batch conv_3d - u8s8f32s32mkl-dnn: IP Batch 1D - u8s8u8s32mkl-dnn: Convolution Batch conv_3d - f32mkl-dnn: IP Batch 1D - u8s8f32s32mkl-dnn: Deconvolution Batch deconv_1d - u8s8u8s32mkl-dnn: Deconvolution Batch deconv_1d - u8s8f32s32mkl-dnn: Deconvolution Batch deconv_1d - f32mkl-dnn: Convolution Batch conv_alexnet - u8s8u8s32mkl-dnn: Convolution Batch conv_alexnet - u8s8f32s32mkl-dnn: Convolution Batch conv_alexnet - f32mkl-dnn: IP Batch 1D - f32mkl-dnn: Deconvolution Batch deconv_3d - u8s8u8s32mkl-dnn: Deconvolution Batch deconv_3d - u8s8f32s32mkl-dnn: Deconvolution Batch deconv_3d - f322 x 828012601300.713823982.359845.716.1621.13101.1720.3820.452607.672633.713.543.293.630.230.230.9514.0619.2448.4211.652256.192181.051.10OpenBenchmarking.org

MKL-DNN

This is a test of the Intel MKL-DNN as the Intel Math Kernel Library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Learn more via the OpenBenchmarking.org test page.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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