Ryzen 5 MKL DNNL

AMD Ryzen 5 3600X 6-Core testing with a MSI X470 GAMING M7 AC (MS-7B77) v1.0 (1.B2 BIOS) and MSI AMD Radeon R7 370 / R9 270/370 OEM 4GB on Ubuntu 18.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/1910068-PTS-RYZEN5MK91.

Ryzen 5 MKL DNNLProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionAMD Ryzen 5 3600X 6-CoreAMD Ryzen 5 3600X 6-Core (6 Cores / 12 Threads)MSI X470 GAMING M7 AC (MS-7B77) v1.0 (1.B2 BIOS)AMD Starship/Matisse16384MB256GB INTEL SSDPEKKW256G7MSI AMD Radeon R7 370 / R9 270/370 OEM 4GBAMD Cape Verde/PitcairnG237HLQualcomm Atheros Killer E2500 + Intel 8265 / 8275Ubuntu 18.045.0.0-29-generic (x86_64)GNOME Shell 3.28.4X Server 1.20.4modesetting 1.20.44.5 Mesa 19.0.8 (LLVM 8.0.0)GCC 7.4.0ext41920x1080OpenBenchmarking.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 - l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional STIBP: always-on RSB filling

Ryzen 5 MKL DNNLlibgav1: Chimera 1080plibgav1: Summer Nature 4Klibgav1: Summer Nature 1080plibgav1: Chimera 1080p 10-bitmkl-dnn: IP Batch 1D - f32mkl-dnn: IP Batch All - f32mkl-dnn: IP Batch 1D - u8s8f32mkl-dnn: IP Batch All - u8s8f32mkl-dnn: Convolution Batch conv_3d - f32mkl-dnn: Convolution Batch conv_all - f32mkl-dnn: Convolution Batch conv_3d - u8s8f32mkl-dnn: Deconvolution Batch deconv_1d - f32mkl-dnn: Deconvolution Batch deconv_3d - f32mkl-dnn: Convolution Batch conv_alexnet - f32mkl-dnn: Convolution Batch conv_all - u8s8f32mkl-dnn: Deconvolution Batch deconv_all - f32mkl-dnn: Deconvolution Batch deconv_1d - u8s8f32mkl-dnn: Deconvolution Batch deconv_3d - u8s8f32mkl-dnn: Recurrent Neural Network Training - f32mkl-dnn: Convolution Batch conv_alexnet - u8s8f32mkl-dnn: Convolution Batch conv_googlenet_v3 - f32mkl-dnn: Convolution Batch conv_googlenet_v3 - u8s8f32AMD Ryzen 5 3600X 6-Core51.6922.7686.3319.296.6830.2874.28330.9327.643666.9316550.877.768.39466.9866429.334056.146808.1311942.27337.098205.12204.953562.16OpenBenchmarking.org

libgav1

Video Input: Chimera 1080p

OpenBenchmarking.orgFPS, More Is Betterlibgav1 2019-10-05Video Input: Chimera 1080pAMD Ryzen 5 3600X 6-Core1224364860SE +/- 0.09, N = 351.691. (CXX) g++ options: -O3 -lpthread

libgav1

Video Input: Summer Nature 4K

OpenBenchmarking.orgFPS, More Is Betterlibgav1 2019-10-05Video Input: Summer Nature 4KAMD Ryzen 5 3600X 6-Core510152025SE +/- 0.01, N = 322.761. (CXX) g++ options: -O3 -lpthread

libgav1

Video Input: Summer Nature 1080p

OpenBenchmarking.orgFPS, More Is Betterlibgav1 2019-10-05Video Input: Summer Nature 1080pAMD Ryzen 5 3600X 6-Core20406080100SE +/- 0.10, N = 386.331. (CXX) g++ options: -O3 -lpthread

libgav1

Video Input: Chimera 1080p 10-bit

OpenBenchmarking.orgFPS, More Is Betterlibgav1 2019-10-05Video Input: Chimera 1080p 10-bitAMD Ryzen 5 3600X 6-Core510152025SE +/- 0.20, N = 319.291. (CXX) g++ options: -O3 -lpthread

MKL-DNN DNNL

Harness: IP Batch 1D - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: IP Batch 1D - Data Type: f32AMD Ryzen 5 3600X 6-Core246810SE +/- 0.02, N = 36.68MIN: 6.51. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: IP Batch All - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: IP Batch All - Data Type: f32AMD Ryzen 5 3600X 6-Core714212835SE +/- 0.03, N = 330.28MIN: 29.921. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: IP Batch 1D - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: IP Batch 1D - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core1632486480SE +/- 0.06, N = 374.28MIN: 72.741. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: IP Batch All - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: IP Batch All - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core70140210280350SE +/- 0.14, N = 3330.93MIN: 328.751. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_3d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_3d - Data Type: f32AMD Ryzen 5 3600X 6-Core714212835SE +/- 0.06, N = 327.64MIN: 27.11. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_all - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_all - Data Type: f32AMD Ryzen 5 3600X 6-Core8001600240032004000SE +/- 8.11, N = 33666.93MIN: 3630.321. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_3d - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_3d - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core4K8K12K16K20KSE +/- 18.31, N = 316550.87MIN: 16508.61. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Deconvolution Batch deconv_1d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Deconvolution Batch deconv_1d - Data Type: f32AMD Ryzen 5 3600X 6-Core246810SE +/- 0.01, N = 37.76MIN: 7.511. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Deconvolution Batch deconv_3d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Deconvolution Batch deconv_3d - Data Type: f32AMD Ryzen 5 3600X 6-Core246810SE +/- 0.01, N = 38.39MIN: 8.121. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_alexnet - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_alexnet - Data Type: f32AMD Ryzen 5 3600X 6-Core100200300400500SE +/- 0.75, N = 3466.98MIN: 464.511. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_all - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_all - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core14K28K42K56K70KSE +/- 170.00, N = 366429.33MIN: 65006.31. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Deconvolution Batch deconv_all - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Deconvolution Batch deconv_all - Data Type: f32AMD Ryzen 5 3600X 6-Core9001800270036004500SE +/- 3.33, N = 34056.14MIN: 3973.181. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core15003000450060007500SE +/- 0.35, N = 36808.13MIN: 6802.681. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core3K6K9K12K15KSE +/- 3.14, N = 311942.27MIN: 11911.71. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Recurrent Neural Network Training - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Recurrent Neural Network Training - Data Type: f32AMD Ryzen 5 3600X 6-Core70140210280350SE +/- 0.27, N = 3337.09MIN: 334.541. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_alexnet - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core2K4K6K8K10KSE +/- 69.37, N = 38205.12MIN: 7943.431. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_googlenet_v3 - Data Type: f32AMD Ryzen 5 3600X 6-Core4080120160200SE +/- 0.54, N = 3204.95MIN: 2021. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

MKL-DNN DNNL

Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetterMKL-DNN DNNL 1.1Harness: Convolution Batch conv_googlenet_v3 - Data Type: u8s8f32AMD Ryzen 5 3600X 6-Core8001600240032004000SE +/- 2.72, N = 33562.16MIN: 3486.381. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

Phoronix Test Suite v10.8.4