slehpc-wk1-ML-05sep2020

VMware testing on SUSE Linux Enterprise High Performance Computing 15 SP2 15.2 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 2009068-NI-SLEHPCWK174
Jump To Table - Results

Statistics

Remove Outliers Before Calculating Averages

Graph Settings

Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
slehpc-wk1-ML-05sep2020
September 06 2020
  4 Hours, 10 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


slehpc-wk1-ML-05sep2020OpenBenchmarking.orgPhoronix Test Suite8 x AMD Ryzen Threadripper 3960X 24-Core (16 Cores)Intel 440BX (6.00 BIOS)Intel 440BX/ZX/DX16GB129GB VMware Virtual SSVGA3D; buildEnsoniq ES1371/ES13732 x Intel 82545EM + 3 x AMD 79c970SUSE Linux Enterprise High Performance Computing 15 SP2 15.25.3.18-24.9-default (x86_64)GNOME Shell 3.34.4X Server2.1 Mesa 19.3.4GCC 7.5.0btrfs1920x984VMwareProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionSystem LayerSlehpc-wk1-ML-05sep2020 BenchmarksSystem Logs- --build=x86_64-suse-linux --disable-libcc1 --disable-libssp --disable-libstdcxx-pch --disable-libvtv --disable-plugin --disable-werror --enable-checking=release --enable-gnu-indirect-function --enable-languages=c,c++,objc,fortran,obj-c++,ada,go --enable-libstdcxx-allocator=new --enable-linux-futex --enable-multilib --enable-offload-targets=hsa,nvptx-none=/usr/nvptx-none, --enable-ssp --enable-version-specific-runtime-libs --host=x86_64-suse-linux --mandir=/usr/share/man --with-arch-32=x86-64 --with-gcc-major-version-only --with-slibdir=/lib64 --with-tune=generic --without-cuda-driver --without-system-libunwind - CPU Microcode: 0x8301039- Python 2.7.17 + Python 3.6.10- 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 STIBP: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected

slehpc-wk1-ML-05sep2020onednn: IP Batch 1D - f32 - CPUonednn: IP Batch All - f32 - CPUonednn: IP Batch 1D - u8s8f32 - CPUonednn: IP Batch All - u8s8f32 - CPUonednn: Convolution Batch Shapes Auto - f32 - CPUonednn: Deconvolution Batch deconv_1d - f32 - CPUonednn: Deconvolution Batch deconv_3d - f32 - CPUonednn: Convolution Batch Shapes Auto - u8s8f32 - CPUonednn: Deconvolution Batch deconv_1d - u8s8f32 - CPUonednn: Deconvolution Batch deconv_3d - u8s8f32 - CPUonednn: Recurrent Neural Network Training - f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUonednn: Matrix Multiply Batch Shapes Transformer - f32 - CPUonednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPUnumpy: deepspeech: tensorflow-lite: SqueezeNettensorflow-lite: Inception V4tensorflow-lite: NASNet Mobiletensorflow-lite: Mobilenet Floattensorflow-lite: Mobilenet Quanttensorflow-lite: Inception ResNet V2plaidml: No - Inference - VGG16 - CPUplaidml: No - Inference - ResNet 50 - CPUnumenta-nab: EXPoSEnumenta-nab: Relative Entropynumenta-nab: Windowed Gaussiannumenta-nab: Earthgecko Skylinenumenta-nab: Bayesian Changepointslehpc-wk1-ML-05sep20204.8392672.87953.0070939.960312.06654.582246.3775612.72317.467005.82675340.82581.20871.519492.93717316.3064.62974143915195733314215097177.2101128176419320.526.87919.44723.76012.072109.21343.979OpenBenchmarking.org

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the oneAPI initiative. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: IP Batch 1D - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep20201.08882.17763.26644.35525.444SE +/- 0.06141, N = 154.83926MIN: 31. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: IP Batch All - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep20201632486480SE +/- 0.38, N = 372.88MIN: 57.471. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPUslehpc-wk1-ML-05sep20200.67661.35322.02982.70643.383SE +/- 0.03928, N = 153.00709MIN: 1.621. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPUslehpc-wk1-ML-05sep2020918273645SE +/- 0.29, N = 339.96MIN: 33.211. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep20203691215SE +/- 0.08, N = 312.07MIN: 10.661. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep20201.0312.0623.0934.1245.155SE +/- 0.03966, N = 154.58224MIN: 3.991. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep2020246810SE +/- 0.03810, N = 36.37756MIN: 5.21. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPUslehpc-wk1-ML-05sep20203691215SE +/- 0.07, N = 312.72MIN: 11.281. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPUslehpc-wk1-ML-05sep2020246810SE +/- 0.12245, N = 157.46700MIN: 5.851. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPUslehpc-wk1-ML-05sep20201.3112.6223.9335.2446.555SE +/- 0.06162, N = 155.82675MIN: 4.781. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep202070140210280350SE +/- 4.59, N = 4340.83MIN: 288.991. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep202020406080100SE +/- 2.01, N = 1281.21MIN: 55.381. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPUslehpc-wk1-ML-05sep20200.34190.68381.02571.36761.7095SE +/- 0.03965, N = 151.51949MIN: 1.11. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 1.5Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPUslehpc-wk1-ML-05sep20200.66091.32181.98272.64363.3045SE +/- 0.02712, N = 32.93717MIN: 2.411. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterNumpy Benchmarkslehpc-wk1-ML-05sep202070140210280350SE +/- 3.95, N = 3316.30

DeepSpeech

Mozilla DeepSpeech is a speech-to-text engine powered by TensorFlow for machine learning and derived from Baidu's Deep Speech research paper. This test profile times the speech-to-text process for a roughly three minute audio recording. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDeepSpeech 0.6slehpc-wk1-ML-05sep20201428425670SE +/- 0.23, N = 364.63

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: SqueezeNetslehpc-wk1-ML-05sep202030K60K90K120K150KSE +/- 193.90, N = 3143915

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4slehpc-wk1-ML-05sep2020400K800K1200K1600K2000KSE +/- 3028.44, N = 31957333

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet Mobileslehpc-wk1-ML-05sep202030K60K90K120K150KSE +/- 102.89, N = 3142150

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet Floatslehpc-wk1-ML-05sep202020K40K60K80K100KSE +/- 169.22, N = 397177.2

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet Quantslehpc-wk1-ML-05sep202020K40K60K80K100KSE +/- 50.21, N = 3101128

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2slehpc-wk1-ML-05sep2020400K800K1200K1600K2000KSE +/- 579.55, N = 31764193

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: CPUslehpc-wk1-ML-05sep2020510152025SE +/- 0.19, N = 320.52

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: ResNet 50 - Device: CPUslehpc-wk1-ML-05sep2020246810SE +/- 0.04, N = 36.87

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: EXPoSEslehpc-wk1-ML-05sep20202004006008001000SE +/- 20.99, N = 9919.45

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Relative Entropyslehpc-wk1-ML-05sep2020612182430SE +/- 0.41, N = 1223.76

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed Gaussianslehpc-wk1-ML-05sep20203691215SE +/- 0.09, N = 312.07

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko Skylineslehpc-wk1-ML-05sep202020406080100SE +/- 0.91, N = 3109.21

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Bayesian Changepointslehpc-wk1-ML-05sep20201020304050SE +/- 0.14, N = 343.98