sle.hpc-wk1-ML-29aug2020 VMware testing on SUSE Linux Enterprise High Performance Computing 15 SP2 15.2 via the Phoronix Test Suite. sle.hpc-wk1-ML-29aug2020: 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: 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: 800x600, System Layer: VMware oneDNN 1.5 Harness: IP Batch 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 4.19208 |=========================================== oneDNN 1.5 Harness: IP Batch All - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 60.42 |============================================= oneDNN 1.5 Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 2.86844 |=========================================== oneDNN 1.5 Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 36.13 |============================================= oneDNN 1.5 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 11.98 |============================================= oneDNN 1.5 Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 4.16513 |=========================================== oneDNN 1.5 Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 6.47745 |=========================================== oneDNN 1.5 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 13.60 |============================================= oneDNN 1.5 Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 6.82040 |=========================================== oneDNN 1.5 Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 5.60745 |=========================================== oneDNN 1.5 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 353.99 |============================================ oneDNN 1.5 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 72.18 |============================================= oneDNN 1.5 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 1.47387 |=========================================== oneDNN 1.5 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 2.70409 |=========================================== Numpy Benchmark Score > Higher Is Better sle.hpc-wk1-ML-29aug2020 . 300.68 |============================================ DeepSpeech 0.6 Seconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 61.73 |============================================= TensorFlow Lite 2020-08-23 Model: SqueezeNet Microseconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 159140 |============================================ TensorFlow Lite 2020-08-23 Model: Inception V4 Microseconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 2189237 |=========================================== TensorFlow Lite 2020-08-23 Model: NASNet Mobile Microseconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 155238 |============================================ TensorFlow Lite 2020-08-23 Model: Mobilenet Float Microseconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 108052 |============================================ TensorFlow Lite 2020-08-23 Model: Mobilenet Quant Microseconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 117076 |============================================ TensorFlow Lite 2020-08-23 Model: Inception ResNet V2 Microseconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 2040520 |=========================================== PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU FPS > Higher Is Better sle.hpc-wk1-ML-29aug2020 . 18.62 |============================================= PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU FPS > Higher Is Better sle.hpc-wk1-ML-29aug2020 . 7.65 |============================================== Numenta Anomaly Benchmark 1.1 Detector: EXPoSE Seconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 792.21 |============================================ Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy Seconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 23.19 |============================================= Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian Seconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 12.64 |============================================= Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline Seconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 116.22 |============================================ Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint Seconds < Lower Is Better sle.hpc-wk1-ML-29aug2020 . 44.49 |=============================================