AMD EPYC 7F32 8-Core testing with a Supermicro H11DSi-NT v2.00 (2.1 BIOS) and llvmpipe on Ubuntu 20.04 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 2012274-HA-EPYC7F32L08
EPYC 7F32 Last
AMD EPYC 7F32 8-Core testing with a Supermicro H11DSi-NT v2.00 (2.1 BIOS) and llvmpipe on Ubuntu 20.04 via the Phoronix Test Suite.
Run 1:
Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: Supermicro H11DSi-NT v2.00 (2.1 BIOS), Chipset: AMD Starship/Matisse, Memory: 64GB, Disk: 280GB INTEL SSDPE21D280GA, Graphics: llvmpipe, Monitor: VE228
OS: Ubuntu 20.04, Kernel: 5.8.0-050800rc6daily20200721-generic (x86_64) 20200720, Desktop: GNOME Shell 3.36.1, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.4 (LLVM 9.0.1 128 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Run 2:
Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: Supermicro H11DSi-NT v2.00 (2.1 BIOS), Chipset: AMD Starship/Matisse, Memory: 64GB, Disk: 280GB INTEL SSDPE21D280GA, Graphics: llvmpipe, Monitor: VE228
OS: Ubuntu 20.04, Kernel: 5.8.0-050800rc6daily20200721-generic (x86_64) 20200720, Desktop: GNOME Shell 3.36.1, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.4 (LLVM 9.0.1 128 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Run 3:
Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: Supermicro H11DSi-NT v2.00 (2.1 BIOS), Chipset: AMD Starship/Matisse, Memory: 64GB, Disk: 280GB INTEL SSDPE21D280GA, Graphics: llvmpipe, Monitor: VE228
OS: Ubuntu 20.04, Kernel: 5.8.0-050800rc6daily20200721-generic (x86_64) 20200720, Desktop: GNOME Shell 3.36.1, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.4 (LLVM 9.0.1 128 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Run 4:
Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: Supermicro H11DSi-NT v2.00 (2.1 BIOS), Chipset: AMD Starship/Matisse, Memory: 64GB, Disk: 280GB INTEL SSDPE21D280GA, Graphics: llvmpipe, Monitor: VE228
OS: Ubuntu 20.04, Kernel: 5.8.0-050800rc6daily20200721-generic (x86_64) 20200720, Desktop: GNOME Shell 3.36.1, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.4 (LLVM 9.0.1 128 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
NCNN 20201218
Target: CPU - Model: googlenet
ms < Lower Is Better
Run 1 . 15.65 |=============================================================
Run 2 . 15.52 |=============================================================
Run 3 . 15.48 |============================================================
Run 4 . 16.38 |================================================================
NCNN 20201218
Target: CPU - Model: squeezenet_ssd
ms < Lower Is Better
Run 1 . 24.86 |===============================================================
Run 2 . 24.48 |==============================================================
Run 3 . 24.46 |==============================================================
Run 4 . 25.31 |================================================================
NCNN 20201218
Target: CPU - Model: mnasnet
ms < Lower Is Better
Run 1 . 6.14 |=================================================================
Run 2 . 5.94 |===============================================================
Run 3 . 5.97 |===============================================================
Run 4 . 6.02 |================================================================
Unpacking The Linux Kernel
linux-4.15.tar.xz
Seconds < Lower Is Better
Run 1 . 5.974 |================================================================
Run 2 . 5.972 |================================================================
Run 3 . 6.016 |================================================================
Run 4 . 5.852 |==============================================================
CLOMP 1.2
Static OMP Speedup
Speedup > Higher Is Better
Run 1 . 29.8 |=================================================================
Run 2 . 29.6 |=================================================================
Run 3 . 29.0 |===============================================================
Run 4 . 29.7 |=================================================================
NCNN 20201218
Target: CPU - Model: yolov4-tiny
ms < Lower Is Better
Run 1 . 27.06 |================================================================
Run 2 . 26.71 |===============================================================
Run 3 . 26.40 |==============================================================
Run 4 . 27.10 |================================================================
oneDNN 2.0
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 9.66757 |==============================================================
Run 2 . 9.62355 |==============================================================
Run 3 . 9.46619 |=============================================================
Run 4 . 9.59529 |==============================================================
oneDNN 2.0
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 6.22116 |==============================================================
Run 2 . 6.15155 |=============================================================
Run 3 . 6.12560 |=============================================================
Run 4 . 6.17937 |==============================================================
NCNN 20201218
Target: CPU - Model: blazeface
ms < Lower Is Better
Run 1 . 3.31 |================================================================
Run 2 . 3.34 |=================================================================
Run 3 . 3.30 |================================================================
Run 4 . 3.31 |================================================================
oneDNN 2.0
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 4.98064 |==============================================================
Run 2 . 4.92337 |=============================================================
Run 3 . 4.95449 |==============================================================
Run 4 . 4.92898 |=============================================================
NCNN 20201218
Target: CPU - Model: efficientnet-b0
ms < Lower Is Better
Run 1 . 10.58 |================================================================
Run 2 . 10.55 |================================================================
Run 3 . 10.46 |===============================================================
Run 4 . 10.48 |===============================================================
oneDNN 2.0
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 0.788963 |============================================================
Run 2 . 0.795590 |=============================================================
Run 3 . 0.797020 |=============================================================
Run 4 . 0.788043 |============================================================
NCNN 20201218
Target: CPU - Model: regnety_400m
ms < Lower Is Better
Run 1 . 32.07 |===============================================================
Run 2 . 32.19 |================================================================
Run 3 . 32.35 |================================================================
Run 4 . 32.03 |===============================================================
NCNN 20201218
Target: CPU-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
Run 1 . 6.66 |=================================================================
Run 2 . 6.64 |=================================================================
Run 3 . 6.62 |=================================================================
Run 4 . 6.60 |================================================================
Unpacking Firefox 84.0
Extracting: firefox-84.0.source.tar.xz
Seconds < Lower Is Better
Run 1 . 20.37 |================================================================
Run 2 . 20.27 |================================================================
Run 3 . 20.22 |================================================================
Run 4 . 20.21 |===============================================================
NCNN 20201218
Target: CPU - Model: resnet18
ms < Lower Is Better
Run 1 . 11.52 |================================================================
Run 2 . 11.57 |================================================================
Run 3 . 11.48 |================================================================
Run 4 . 11.57 |================================================================
oneDNN 2.0
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 3417.91 |==============================================================
Run 2 . 3441.93 |==============================================================
Run 3 . 3441.20 |==============================================================
Run 4 . 3421.95 |==============================================================
NCNN 20201218
Target: CPU - Model: mobilenet
ms < Lower Is Better
Run 1 . 19.94 |================================================================
Run 2 . 19.81 |================================================================
Run 3 . 19.89 |================================================================
Run 4 . 19.88 |================================================================
NCNN 20201218
Target: CPU - Model: resnet50
ms < Lower Is Better
Run 1 . 23.02 |================================================================
Run 2 . 22.96 |================================================================
Run 3 . 22.89 |================================================================
Run 4 . 23.04 |================================================================
oneDNN 2.0
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 4.94409 |==============================================================
Run 2 . 4.96823 |==============================================================
Run 3 . 4.95793 |==============================================================
Run 4 . 4.93690 |==============================================================
oneDNN 2.0
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 1704.97 |==============================================================
Run 2 . 1715.65 |==============================================================
Run 3 . 1712.85 |==============================================================
Run 4 . 1714.22 |==============================================================
Build2 0.13
Time To Compile
Seconds < Lower Is Better
Run 1 . 112.08 |===============================================================
Run 2 . 112.78 |===============================================================
Run 3 . 112.67 |===============================================================
Run 4 . 112.46 |===============================================================
NCNN 20201218
Target: CPU-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
Run 1 . 6.87 |=================================================================
Run 2 . 6.84 |=================================================================
Run 3 . 6.85 |=================================================================
Run 4 . 6.83 |=================================================================
oneDNN 2.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 1.16439 |==============================================================
Run 2 . 1.15868 |==============================================================
Run 3 . 1.15947 |==============================================================
Run 4 . 1.16157 |==============================================================
NCNN 20201218
Target: CPU - Model: vgg16
ms < Lower Is Better
Run 1 . 32.45 |================================================================
Run 2 . 32.41 |================================================================
Run 3 . 32.32 |================================================================
Run 4 . 32.31 |================================================================
oneDNN 2.0
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 1711.39 |==============================================================
Run 2 . 1718.14 |==============================================================
Run 3 . 1716.53 |==============================================================
Run 4 . 1711.28 |==============================================================
oneDNN 2.0
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 3429.54 |==============================================================
Run 2 . 3438.99 |==============================================================
Run 3 . 3436.78 |==============================================================
Run 4 . 3427.26 |==============================================================
oneDNN 2.0
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 7.20000 |==============================================================
Run 2 . 7.21888 |==============================================================
Run 3 . 7.22277 |==============================================================
Run 4 . 7.22008 |==============================================================
NCNN 20201218
Target: CPU - Model: shufflenet-v2
ms < Lower Is Better
Run 1 . 9.61 |=================================================================
Run 2 . 9.63 |=================================================================
Run 3 . 9.60 |=================================================================
Run 4 . 9.60 |=================================================================
oneDNN 2.0
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 3.54939 |==============================================================
Run 2 . 3.55093 |==============================================================
Run 3 . 3.55967 |==============================================================
Run 4 . 3.55938 |==============================================================
NCNN 20201218
Target: CPU - Model: alexnet
ms < Lower Is Better
Run 1 . 7.58 |=================================================================
Run 2 . 7.60 |=================================================================
Run 3 . 7.60 |=================================================================
Run 4 . 7.59 |=================================================================
Timed Eigen Compilation 3.3.9
Time To Compile
Seconds < Lower Is Better
Run 1 . 82.88 |================================================================
Run 2 . 82.95 |================================================================
Run 3 . 83.07 |================================================================
Run 4 . 82.99 |================================================================
oneDNN 2.0
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 1708.29 |==============================================================
Run 2 . 1708.22 |==============================================================
Run 3 . 1711.14 |==============================================================
Run 4 . 1711.87 |==============================================================
oneDNN 2.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 3.59741 |==============================================================
Run 2 . 3.59581 |==============================================================
Run 3 . 3.59103 |==============================================================
Run 4 . 3.59799 |==============================================================
Monkey Audio Encoding 3.99.6
WAV To APE
Seconds < Lower Is Better
Run 1 . 12.51 |================================================================
Run 2 . 12.51 |================================================================
Run 3 . 12.49 |================================================================
Run 4 . 12.49 |================================================================
oneDNN 2.0
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 5.58298 |==============================================================
Run 2 . 5.57986 |==============================================================
Run 3 . 5.57860 |==============================================================
Run 4 . 5.58763 |==============================================================
Ogg Audio Encoding 1.3.4
WAV To Ogg
Seconds < Lower Is Better
Run 1 . 20.57 |================================================================
Run 2 . 20.57 |================================================================
Run 3 . 20.58 |================================================================
Run 4 . 20.56 |================================================================
oneDNN 2.0
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 2.79140 |==============================================================
Run 2 . 2.78976 |==============================================================
Run 3 . 2.79003 |==============================================================
Run 4 . 2.79287 |==============================================================
oneDNN 2.0
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 6.42420 |==============================================================
Run 2 . 6.42196 |==============================================================
Run 3 . 6.42311 |==============================================================
Run 4 . 6.41776 |==============================================================
Opus Codec Encoding 1.3.1
WAV To Opus Encode
Seconds < Lower Is Better
Run 1 . 7.972 |================================================================
Run 2 . 7.973 |================================================================
Run 3 . 7.969 |================================================================
Run 4 . 7.966 |================================================================
WavPack Audio Encoding 5.3
WAV To WavPack
Seconds < Lower Is Better
Run 1 . 13.73 |================================================================
Run 2 . 13.73 |================================================================
Run 3 . 13.73 |================================================================
Run 4 . 13.73 |================================================================
oneDNN 2.0
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 3604.40 |==============================================================
Run 2 . 3436.43 |===========================================================
Run 3 . 3431.50 |===========================================================
Run 4 . 3417.31 |===========================================================