new-tests-epyc

2 x AMD EPYC 7F72 24-Core testing with a AMD DAYTONA_X (RDY1006G BIOS) and ASPEED on Ubuntu 18.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2004292-NI-NEWTESTSE05.

new-tests-epyc ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverCompilerFile-SystemScreen ResolutionAMD EPYC 7452 32-CoreAMD EPYC 7452 32-Core - ASPEED - AMD DAYTONA_X2 x EPYC 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2PAMD 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 504GB252GBASPEEDAMD EPYC 7232P 8-Core @ 3.10GHz (8 Cores / 16 Threads)126GB252GBAMD EPYC 7742 64-Core @ 2.25GHz (64 Cores / 128 Threads)AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads)2 x AMD EPYC 7F32 8-Core @ 3.70GHz (16 Cores / 32 Threads)504GBAMD EPYC 7F72 24-Core @ 3.20GHz (24 Cores / 48 Threads)252GB2 x AMD EPYC 7F72 24-Core @ 3.20GHz (48 Cores / 96 Threads)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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P1.7133523.920413.535856.23712.118153.6829643.05852.04794239.64243.66672.98562.8762.9792.4928537.65901.8565220.49763.293724.4806769.54393.24097285.52246.16022.23262.0522.2322.4654973.37952.0251220.68953.405414.5586469.84243.48241347.31955.34522.00362.9622.0075.6956668.27993.3106444.11745.455498.07177146.6766.92182310.49341.01420.81466.6090.8126.9595161.12643.3690743.01015.573318.21848148.7986.83223309.69239.14030.99566.5170.9961.5324517.350125.179887.97872.021272.6536223.81461.41346350.22475.02214.79962.0524.8063.4822246.84282.7460133.93874.513456.34519120.4605.53460267.56333.10001.36754.6771.3652.1294831.86071.6388417.91202.848944.1146760.80812.87436267.20448.39092.51454.6522.5151.6351124.266212.272251.36682.137223.2385645.10462.16626219.99138.10823.11757.3553.1152.0219717.924222.308779.87492.113152.0107522.95931.37813373.86787.86115.70557.4655.704OpenBenchmarking.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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P246810SE +/- 0.00424, N = 3SE +/- 0.02763, N = 15SE +/- 0.02772, N = 7SE +/- 0.00498, N = 3SE +/- 2.22474, N = 15SE +/- 0.01951, N = 4SE +/- 0.00139, N = 3SE +/- 0.02920, N = 15SE +/- 0.00915, N = 3SE +/- 0.32289, N = 121.713352.492852.465495.695666.959511.532453.482222.129481.635112.02197MIN: 1.52MIN: 2.1MIN: 2.14MIN: 5.43MIN: 4.35MIN: 1.35MIN: 3.37MIN: 1.84MIN: 1.55MIN: 1.211. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P1632486480SE +/- 0.02, N = 3SE +/- 0.64, N = 15SE +/- 1.11, N = 15SE +/- 0.07, N = 3SE +/- 0.05, N = 3SE +/- 0.08, N = 3SE +/- 0.01, N = 3SE +/- 0.16, N = 3SE +/- 0.02, N = 3SE +/- 0.18, N = 323.9237.6673.3868.2861.1317.3546.8431.8624.2717.92MIN: 22.68MIN: 34.37MIN: 60.33MIN: 65.55MIN: 57.2MIN: 15.72MIN: 45.5MIN: 30.86MIN: 23.46MIN: 15.531. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P612182430SE +/- 0.00501, N = 3SE +/- 0.01792, N = 3SE +/- 0.02707, N = 15SE +/- 0.00260, N = 3SE +/- 0.00510, N = 3SE +/- 0.06197, N = 3SE +/- 0.00311, N = 3SE +/- 0.02655, N = 3SE +/- 0.01654, N = 3SE +/- 0.08032, N = 313.535801.856522.025123.310643.3690725.179802.746011.6388412.2722022.30870MIN: 8.64MIN: 23.6MIN: 6.89MIN: 18.971. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P20406080100SE +/- 0.03, N = 3SE +/- 0.12, N = 3SE +/- 0.19, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.15, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.53, N = 356.2420.5020.6944.1243.0187.9833.9417.9151.3779.87MIN: 45.39MIN: 19.94MIN: 19.95MIN: 43.46MIN: 42.03MIN: 80.59MIN: 33.33MIN: 17.5MIN: 35.98MIN: 70.231. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P1.2542.5083.7625.0166.27SE +/- 0.00397, N = 3SE +/- 0.03501, N = 15SE +/- 0.03272, N = 15SE +/- 0.03963, N = 3SE +/- 0.04859, N = 3SE +/- 0.01860, N = 15SE +/- 0.04296, N = 3SE +/- 0.03053, N = 15SE +/- 0.02912, N = 3SE +/- 0.04533, N = 152.118153.293723.405415.455495.573312.021274.513452.848942.137222.11315MIN: 1.96MIN: 2.85MIN: 2.89MIN: 5.23MIN: 5.22MIN: 1.76MIN: 4.38MIN: 2.53MIN: 1.99MIN: 1.721. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P246810SE +/- 0.00936, N = 3SE +/- 0.02841, N = 3SE +/- 0.02833, N = 3SE +/- 0.02188, N = 3SE +/- 0.01268, N = 3SE +/- 0.03001, N = 15SE +/- 0.01747, N = 3SE +/- 0.05522, N = 4SE +/- 0.00622, N = 3SE +/- 0.00054, N = 33.682964.480674.558648.071778.218482.653626.345194.114673.238562.01075MIN: 3.39MIN: 4.19MIN: 4.26MIN: 7.82MIN: 7.89MIN: 2.31MIN: 6.28MIN: 3.64MIN: 2.98MIN: 1.931. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P306090120150SE +/- 0.18, N = 3SE +/- 0.09, N = 3SE +/- 0.14, N = 3SE +/- 0.01, N = 3SE +/- 0.45, N = 3SE +/- 0.01, N = 3SE +/- 0.11, N = 3SE +/- 0.16, N = 3SE +/- 0.07, N = 3SE +/- 0.19, N = 343.0669.5469.84146.68148.8023.81120.4660.8145.1022.96MIN: 41.58MIN: 69.18MIN: 69.22MIN: 146.21MIN: 146.28MIN: 22.74MIN: 120.06MIN: 60.33MIN: 44.07MIN: 22.171. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P246810SE +/- 0.00367, N = 3SE +/- 0.00720, N = 3SE +/- 0.00486, N = 3SE +/- 0.00745, N = 3SE +/- 0.02503, N = 3SE +/- 0.02402, N = 3SE +/- 0.00115, N = 3SE +/- 0.00379, N = 3SE +/- 0.00359, N = 3SE +/- 0.01810, N = 152.047943.240973.482416.921826.832231.413465.534602.874362.166261.37813MIN: 1.84MIN: 3.13MIN: 3.32MIN: 6.88MIN: 6.71MIN: 5.48MIN: 2.77MIN: 2.081. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P80160240320400SE +/- 0.42, N = 3SE +/- 3.80, N = 15SE +/- 4.77, N = 3SE +/- 0.66, N = 3SE +/- 0.65, N = 3SE +/- 0.79, N = 3SE +/- 0.38, N = 3SE +/- 3.54, N = 15SE +/- 0.75, N = 3SE +/- 1.73, N = 3239.64285.52347.32310.49309.69350.22267.56267.20219.99373.87MIN: 235.95MIN: 261.39MIN: 316.21MIN: 302.23MIN: 298MIN: 338.9MIN: 264.4MIN: 238.63MIN: 212.32MIN: 347.461. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P20406080100SE +/- 0.28, N = 3SE +/- 0.43, N = 3SE +/- 0.83, N = 3SE +/- 0.08, N = 3SE +/- 0.55, N = 3SE +/- 0.65, N = 3SE +/- 0.12, N = 3SE +/- 1.01, N = 14SE +/- 0.21, N = 3SE +/- 1.17, N = 1543.6746.1655.3541.0139.1475.0233.1048.3938.1187.86MIN: 42.41MIN: 42.94MIN: 46.42MIN: 39.59MIN: 36.32MIN: 71.74MIN: 32.6MIN: 41.21MIN: 36.64MIN: 73.431. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P1.28362.56723.85085.13446.418SE +/- 0.003, N = 3SE +/- 0.002, N = 3SE +/- 0.003, N = 3SE +/- 0.001, N = 3SE +/- 0.003, N = 3SE +/- 0.004, N = 3SE +/- 0.001, N = 3SE +/- 0.002, N = 3SE +/- 0.009, N = 3SE +/- 0.004, N = 32.9852.2322.0030.8140.9954.7991.3672.5143.1175.7051. (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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P1530456075SE +/- 0.09, N = 3SE +/- 0.06, N = 3SE +/- 0.02, N = 3SE +/- 0.09, N = 3SE +/- 0.11, N = 3SE +/- 0.11, N = 3SE +/- 0.18, N = 3SE +/- 0.16, N = 3SE +/- 0.05, N = 3SE +/- 0.05, N = 362.8862.0562.9666.6166.5262.0554.6854.6557.3657.471. 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 72622 x EPYC 7262 2P 4cEPYC 7232 2P 4cEPYC 7232PEPYC 7742EPYC 7F32EPYC 7F32 2PEPYC 7F72EPYC 7F72 2P1.28342.56683.85025.13366.417SE +/- 0.005, N = 3SE +/- 0.001, N = 3SE +/- 0.003, N = 3SE +/- 0.001, N = 3SE +/- 0.001, N = 3SE +/- 0.005, N = 3SE +/- 0.001, N = 3SE +/- 0.005, N = 3SE +/- 0.009, N = 3SE +/- 0.016, N = 32.9792.2322.0070.8120.9964.8061.3652.5153.1155.7041. (CXX) g++ options: -O3 -pthread -lrt -lpthread -lm

Phoronix Test Suite v10.8.4