new-tests-epyc

2 x AMD EPYC 7262 8-Core testing with a AMD DAYTONA_X (RDY1006G BIOS) and llvmpipe 504GB on Ubuntu 18.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2004158-NI-NEWTESTSE84.

new-tests-epyc ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverCompilerFile-SystemScreen ResolutionAMD EPYC 7452 32-CoreAMD EPYC 7452 32-Core - ASPEED - AMD DAYTONA_X2 x EPYC 7262AMD EPYC 7452 32-Core @ 2.35GHz (32 Cores / 64 Threads)AMD DAYTONA_X (RDY1006G BIOS)AMD Device 1480252GB3841GB Micron_9300_MTFDHAL3T8TDPASPEEDVE2282 x Mellanox MT27710Ubuntu 18.045.3.0-40-generic (x86_64)GNOME Shell 3.28.4X Server 1.20.5modesetting 1.20.5GCC 7.4.0ext41920x10802 x AMD EPYC 7262 8-Core @ 3.20GHz (16 Cores / 32 Threads)504GBllvmpipe 504GBOpenBenchmarking.orgCompiler Details- --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 Processor Details- Scaling Governor: acpi-cpufreq performance - CPU Microcode: 0x8301034Security Details- itlb_multihit: Not affected + 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 IBRS_FW STIBP: conditional RSB filling + tsx_async_abort: Not affected

new-tests-epyc mkl-dnn: IP Batch 1D - f32mkl-dnn: IP Batch All - f32mkl-dnn: IP Batch 1D - u8s8f32mkl-dnn: IP Batch All - u8s8f32mkl-dnn: Deconvolution Batch deconv_1d - f32mkl-dnn: Deconvolution Batch deconv_3d - f32mkl-dnn: Deconvolution Batch deconv_1d - u8s8f32mkl-dnn: Deconvolution Batch deconv_3d - u8s8f32mkl-dnn: Recurrent Neural Network Training - f32mkl-dnn: Recurrent Neural Network Inference - f32gromacs: Water Benchmarkgit: Time To Complete Common Git Commandsgromacs: Water BenchmarkAMD EPYC 7452 32-CoreAMD EPYC 7452 32-Core - ASPEED - AMD DAYTONA_X2 x EPYC 72621.7133523.920413.535856.23712.118153.6829643.05852.04794239.64243.66672.98562.8762.9792.4928537.65901.8565220.49763.293724.4806769.54393.24097285.52246.16022.23262.0522.232OpenBenchmarking.org

oneDNN MKL-DNN

Harness: IP Batch 1D - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: IP Batch 1D - Data Type: f32AMD EPYC 7452 32-Core2 x EPYC 72620.56091.12181.68272.24362.8045SE +/- 0.00424, N = 3SE +/- 0.02763, N = 151.713352.49285MIN: 1.52MIN: 2.11. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: IP Batch All - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: IP Batch All - Data Type: f32AMD EPYC 7452 32-Core2 x EPYC 7262918273645SE +/- 0.02, N = 3SE +/- 0.64, N = 1523.9237.66MIN: 22.68MIN: 34.371. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: IP Batch 1D - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: IP Batch 1D - Data Type: u8s8f32AMD EPYC 7452 32-Core2 x EPYC 72623691215SE +/- 0.00501, N = 3SE +/- 0.01792, N = 313.535801.85652MIN: 8.641. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: IP Batch All - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: IP Batch All - Data Type: u8s8f32AMD EPYC 7452 32-Core2 x EPYC 72621326395265SE +/- 0.03, N = 3SE +/- 0.12, N = 356.2420.50MIN: 45.39MIN: 19.941. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: Deconvolution Batch deconv_1d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Deconvolution Batch deconv_1d - Data Type: f32AMD EPYC 7452 32-Core2 x EPYC 72620.74111.48222.22332.96443.7055SE +/- 0.00397, N = 3SE +/- 0.03501, N = 152.118153.29372MIN: 1.96MIN: 2.851. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: Deconvolution Batch deconv_3d - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Deconvolution Batch deconv_3d - Data Type: f32AMD EPYC 7452 32-Core2 x EPYC 72621.00822.01643.02464.03285.041SE +/- 0.00936, N = 3SE +/- 0.02841, N = 33.682964.48067MIN: 3.39MIN: 4.191. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32AMD EPYC 7452 32-Core2 x EPYC 72621530456075SE +/- 0.18, N = 3SE +/- 0.09, N = 343.0669.54MIN: 41.58MIN: 69.181. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32AMD EPYC 7452 32-Core2 x EPYC 72620.72921.45842.18762.91683.646SE +/- 0.00367, N = 3SE +/- 0.00720, N = 32.047943.24097MIN: 1.84MIN: 3.131. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: Recurrent Neural Network Training - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Recurrent Neural Network Training - Data Type: f32AMD EPYC 7452 32-Core2 x EPYC 726260120180240300SE +/- 0.42, N = 3SE +/- 3.80, N = 15239.64285.52MIN: 235.95MIN: 261.391. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

oneDNN MKL-DNN

Harness: Recurrent Neural Network Inference - Data Type: f32

OpenBenchmarking.orgms, Fewer Is BetteroneDNN MKL-DNN 1.3Harness: Recurrent Neural Network Inference - Data Type: f32AMD EPYC 7452 32-Core2 x EPYC 72621020304050SE +/- 0.28, N = 3SE +/- 0.43, N = 343.6746.16MIN: 42.41MIN: 42.941. (CXX) g++ options: -O3 -march=native -std=c++11 -msse4.1 -fPIC -fopenmp -pie -lpthread -ldl

GROMACS

Water Benchmark

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2020Water BenchmarkAMD EPYC 7452 32-Core2 x EPYC 72620.67161.34322.01482.68643.358SE +/- 0.003, N = 3SE +/- 0.002, N = 32.9852.2321. (CXX) g++ options: -O3 -pthread -lrt -lpthread -lm

Git

Time To Complete Common Git Commands

OpenBenchmarking.orgSeconds, Fewer Is BetterGitTime To Complete Common Git CommandsAMD EPYC 7452 32-Core2 x EPYC 72621428425670SE +/- 0.09, N = 3SE +/- 0.06, N = 362.8862.051. git version 2.17.1

GROMACS

Water Benchmark

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2020.1Water BenchmarkAMD EPYC 7452 32-Core - ASPEED - AMD DAYTONA_X2 x EPYC 72620.67031.34062.01092.68123.3515SE +/- 0.005, N = 3SE +/- 0.001, N = 32.9792.2321. (CXX) g++ options: -O3 -pthread -lrt -lpthread -lm

Phoronix Test Suite v10.8.4