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
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Result
Identifier
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Performance Per
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Date
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  Test
  Duration
slehpc-wk1-ML-05sep2020
September 06 2020
  4 Hours, 10 Minutes
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slehpc-wk1-ML-05sep2020 VMware testing on SUSE Linux Enterprise High Performance Computing 15 SP2 15.2 via the Phoronix Test Suite. ,,"slehpc-wk1-ML-05sep2020" Processor,,8 x AMD Ryzen Threadripper 3960X 24-Core (16 Cores) Motherboard,,Intel 440BX (6.00 BIOS) Chipset,,Intel 440BX/ZX/DX Memory,,16GB Disk,,129GB VMware Virtual S Graphics,,SVGA3D; build: RELEASE; LLVM; Audio,,Ensoniq ES1371/ES1373 Network,,2 x Intel 82545EM + 3 x AMD 79c970 OS,,SUSE Linux Enterprise High Performance Computing 15 SP2 15.2 Kernel,,5.3.18-24.9-default (x86_64) Desktop,,GNOME Shell 3.34.4 Display Server,,X Server OpenGL,,2.1 Mesa 19.3.4 Compiler,,GCC 7.5.0 File-System,,btrfs Screen Resolution,,1920x984 System Layer,,VMware ,,"slehpc-wk1-ML-05sep2020" "PlaidML - FP16: No - Mode: Inference - Network: VGG16 - Device: CPU (FPS)",HIB,20.52 "PlaidML - FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU (FPS)",HIB,6.87 "Numpy Benchmark - (Score)",HIB,316.30 "TensorFlow Lite - Model: SqueezeNet (us)",LIB,143915 "TensorFlow Lite - Model: Inception V4 (us)",LIB,1957333 "TensorFlow Lite - Model: NASNet Mobile (us)",LIB,142150 "TensorFlow Lite - Model: Mobilenet Float (us)",LIB,97177.2 "TensorFlow Lite - Model: Mobilenet Quant (us)",LIB,101128 "TensorFlow Lite - Model: Inception ResNet V2 (us)",LIB,1764193 "oneDNN - Harness: IP Batch 1D - Data Type: f32 - Engine: CPU (ms)",LIB,4.83926 "oneDNN - Harness: IP Batch All - Data Type: f32 - Engine: CPU (ms)",LIB,72.8795 "oneDNN - Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.00709 "oneDNN - Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,39.9603 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,12.0665 "oneDNN - Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU (ms)",LIB,4.58224 "oneDNN - Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU (ms)",LIB,6.37756 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,12.7231 "oneDNN - Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7.46700 "oneDNN - Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5.82675 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,340.825 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,81.2087 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,1.51949 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.93717 "DeepSpeech - (sec)",LIB,64.62974 "Numenta Anomaly Benchmark - Detector: EXPoSE (sec)",LIB,919.447 "Numenta Anomaly Benchmark - Detector: Relative Entropy (sec)",LIB,23.760 "Numenta Anomaly Benchmark - Detector: Windowed Gaussian (sec)",LIB,12.072 "Numenta Anomaly Benchmark - Detector: Earthgecko Skyline (sec)",LIB,109.213 "Numenta Anomaly Benchmark - Detector: Bayesian Changepoint (sec)",LIB,43.979