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 slehpc-wk1-ML-05sep2020 - Phoronix Test Suite slehpc-wk1-ML-05sep2020 VMware testing on SUSE Linux Enterprise High Performance Computing 15 SP2 15.2 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2009068-NI-SLEHPCWK174&grt .
slehpc-wk1-ML-05sep2020 Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Compiler File-System Screen Resolution System Layer slehpc-wk1-ML-05sep2020 8 x AMD Ryzen Threadripper 3960X 24-Core (16 Cores) Intel 440BX (6.00 BIOS) Intel 440BX/ZX/DX 16GB 129GB VMware Virtual S SVGA3D; build: RELEASE; LLVM; Ensoniq ES1371/ES1373 2 x Intel 82545EM + 3 x AMD 79c970 SUSE Linux Enterprise High Performance Computing 15 SP2 15.2 5.3.18-24.9-default (x86_64) GNOME Shell 3.34.4 X Server 2.1 Mesa 19.3.4 GCC 7.5.0 btrfs 1920x984 VMware OpenBenchmarking.org - --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-05sep2020 deepspeech: numenta-nab: EXPoSE numenta-nab: Relative Entropy numenta-nab: Windowed Gaussian numenta-nab: Earthgecko Skyline numenta-nab: Bayesian Changepoint numpy: onednn: IP Batch 1D - f32 - CPU onednn: IP Batch All - f32 - CPU onednn: IP Batch 1D - u8s8f32 - CPU onednn: IP Batch All - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch deconv_1d - f32 - CPU onednn: Deconvolution Batch deconv_3d - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Deconvolution Batch deconv_1d - u8s8f32 - CPU onednn: Deconvolution Batch deconv_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU plaidml: No - Inference - VGG16 - CPU plaidml: No - Inference - ResNet 50 - CPU tensorflow-lite: SqueezeNet tensorflow-lite: Inception V4 tensorflow-lite: NASNet Mobile tensorflow-lite: Mobilenet Float tensorflow-lite: Mobilenet Quant tensorflow-lite: Inception ResNet V2 slehpc-wk1-ML-05sep2020 64.62974 919.447 23.760 12.072 109.213 43.979 316.30 4.83926 72.8795 3.00709 39.9603 12.0665 4.58224 6.37756 12.7231 7.46700 5.82675 340.825 81.2087 1.51949 2.93717 20.52 6.87 143915 1957333 142150 97177.2 101128 1764193 OpenBenchmarking.org
DeepSpeech OpenBenchmarking.org Seconds, Fewer Is Better DeepSpeech 0.6 slehpc-wk1-ML-05sep2020 14 28 42 56 70 SE +/- 0.23, N = 3 64.63
Numenta Anomaly Benchmark Detector: EXPoSE OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: EXPoSE slehpc-wk1-ML-05sep2020 200 400 600 800 1000 SE +/- 20.99, N = 9 919.45
Numenta Anomaly Benchmark Detector: Relative Entropy OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy slehpc-wk1-ML-05sep2020 6 12 18 24 30 SE +/- 0.41, N = 12 23.76
Numenta Anomaly Benchmark Detector: Windowed Gaussian OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian slehpc-wk1-ML-05sep2020 3 6 9 12 15 SE +/- 0.09, N = 3 12.07
Numenta Anomaly Benchmark Detector: Earthgecko Skyline OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline slehpc-wk1-ML-05sep2020 20 40 60 80 100 SE +/- 0.91, N = 3 109.21
Numenta Anomaly Benchmark Detector: Bayesian Changepoint OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint slehpc-wk1-ML-05sep2020 10 20 30 40 50 SE +/- 0.14, N = 3 43.98
Numpy Benchmark OpenBenchmarking.org Score, More Is Better Numpy Benchmark slehpc-wk1-ML-05sep2020 70 140 210 280 350 SE +/- 3.95, N = 3 316.30
oneDNN Harness: IP Batch 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch 1D - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 1.0888 2.1776 3.2664 4.3552 5.444 SE +/- 0.06141, N = 15 4.83926 MIN: 3 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: IP Batch All - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch All - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 16 32 48 64 80 SE +/- 0.38, N = 3 72.88 MIN: 57.47 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU slehpc-wk1-ML-05sep2020 0.6766 1.3532 2.0298 2.7064 3.383 SE +/- 0.03928, N = 15 3.00709 MIN: 1.62 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU slehpc-wk1-ML-05sep2020 9 18 27 36 45 SE +/- 0.29, N = 3 39.96 MIN: 33.21 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 3 6 9 12 15 SE +/- 0.08, N = 3 12.07 MIN: 10.66 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 1.031 2.062 3.093 4.124 5.155 SE +/- 0.03966, N = 15 4.58224 MIN: 3.99 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 2 4 6 8 10 SE +/- 0.03810, N = 3 6.37756 MIN: 5.2 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU slehpc-wk1-ML-05sep2020 3 6 9 12 15 SE +/- 0.07, N = 3 12.72 MIN: 11.28 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU slehpc-wk1-ML-05sep2020 2 4 6 8 10 SE +/- 0.12245, N = 15 7.46700 MIN: 5.85 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU slehpc-wk1-ML-05sep2020 1.311 2.622 3.933 5.244 6.555 SE +/- 0.06162, N = 15 5.82675 MIN: 4.78 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 70 140 210 280 350 SE +/- 4.59, N = 4 340.83 MIN: 288.99 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 20 40 60 80 100 SE +/- 2.01, N = 12 81.21 MIN: 55.38 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU slehpc-wk1-ML-05sep2020 0.3419 0.6838 1.0257 1.3676 1.7095 SE +/- 0.03965, N = 15 1.51949 MIN: 1.1 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 1.5 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU slehpc-wk1-ML-05sep2020 0.6609 1.3218 1.9827 2.6436 3.3045 SE +/- 0.02712, N = 3 2.93717 MIN: 2.41 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU slehpc-wk1-ML-05sep2020 5 10 15 20 25 SE +/- 0.19, N = 3 20.52
PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU slehpc-wk1-ML-05sep2020 2 4 6 8 10 SE +/- 0.04, N = 3 6.87
TensorFlow Lite Model: SqueezeNet OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: SqueezeNet slehpc-wk1-ML-05sep2020 30K 60K 90K 120K 150K SE +/- 193.90, N = 3 143915
TensorFlow Lite Model: Inception V4 OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception V4 slehpc-wk1-ML-05sep2020 400K 800K 1200K 1600K 2000K SE +/- 3028.44, N = 3 1957333
TensorFlow Lite Model: NASNet Mobile OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: NASNet Mobile slehpc-wk1-ML-05sep2020 30K 60K 90K 120K 150K SE +/- 102.89, N = 3 142150
TensorFlow Lite Model: Mobilenet Float OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Float slehpc-wk1-ML-05sep2020 20K 40K 60K 80K 100K SE +/- 169.22, N = 3 97177.2
TensorFlow Lite Model: Mobilenet Quant OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Quant slehpc-wk1-ML-05sep2020 20K 40K 60K 80K 100K SE +/- 50.21, N = 3 101128
TensorFlow Lite Model: Inception ResNet V2 OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception ResNet V2 slehpc-wk1-ML-05sep2020 400K 800K 1200K 1600K 2000K SE +/- 579.55, N = 3 1764193
Phoronix Test Suite v10.8.4