epyc sep

2 x AMD EPYC 7713 64-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 22.04 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 2209053-NE-EPYCSEP9279
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A
September 05 2022
  1 Hour, 38 Minutes
N
September 05 2022
  1 Hour, 19 Minutes
C
September 05 2022
  1 Hour, 41 Minutes
D
September 05 2022
  1 Hour, 16 Minutes
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epyc sep 2 x AMD EPYC 7713 64-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite. ,,"A","N","C","D" Processor,,2 x AMD EPYC 7713 64-Core @ 2.00GHz (128 Cores / 256 Threads),2 x AMD EPYC 7713 64-Core @ 2.00GHz (128 Cores / 256 Threads),2 x AMD EPYC 7713 64-Core @ 2.00GHz (128 Cores / 256 Threads),2 x AMD EPYC 7713 64-Core @ 2.00GHz (128 Cores / 256 Threads) Motherboard,,AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS) Chipset,,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse Memory,,512GB,512GB,512GB,512GB Disk,,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP Graphics,,ASPEED,ASPEED,ASPEED,ASPEED Monitor,,VE228,VE228,VE228,VE228 Network,,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710,2 x Mellanox MT27710 OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.19.0-051900daily20220803-generic (x86_64),5.19.0-051900daily20220803-generic (x86_64),5.19.0-051900daily20220803-generic (x86_64),5.19.0-051900daily20220803-generic (x86_64) Desktop,,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4 Display Server,,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3 Vulkan,,1.2.204,1.2.204,1.2.204,1.2.204 Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0 File-System,,ext4,ext4,ext4,ext4 Screen Resolution,,1920x1080,1920x1080,1920x1080,1920x1080 ,,"A","N","C","D" "Mobile Neural Network - Model: nasnet (ms)",LIB,93.47,33.35,107.171,21.335 "Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,3.283,4.456,9.549,2.881 "Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,11.919,5.207,5.101,5.132 "GraphicsMagick - Operation: Rotate (Iterations/min)",HIB,568,738,721,723 "GraphicsMagick - Operation: HWB Color Space (Iterations/min)",HIB,1039,1031,1107,873 "GraphicsMagick - Operation: Resizing (Iterations/min)",HIB,130,117,113,109 "Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,5.209,4.465,4.9,4.779 "Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,7.738,8.859,8.767,8.766 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,2.06,1.94,1.96,2.13 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,59076.88,62630.27,61415.85,57587.74 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,3.01,3.19,3.13,2.99 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,41358.65,39273.79,39955.31,41518.27 "GraphicsMagick - Operation: Noise-Gaussian (Iterations/min)",HIB,780,824,782,811 "Natron - Input: Spaceship (FPS)",HIB,1.9,1.9,1.8,1.8 "Timed Erlang/OTP Compilation - Time To Compile (sec)",LIB,100.236,98.272,101.425,103.687 "Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,6.867,6.611,6.568,6.576 "Unpacking The Linux Kernel - linux-5.19.tar.xz (sec)",LIB,6.946,6.87,6.823,7.088 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,637290,635891,621945,641048 "Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,25.463,26.045,25.342,26.032 "Mobile Neural Network - Model: inception-v3 (ms)",LIB,30.499,29.84,30.645,30.203 "Timed Node.js Compilation - Time To Compile (sec)",LIB,111.334,113.809,112.73,113.844 "GraphicsMagick - Operation: Enhanced (Iterations/min)",HIB,1377,1366,1355,1355 "GraphicsMagick - Operation: Sharpen (Iterations/min)",HIB,784,776,773,772 "GraphicsMagick - Operation: Swirl (Iterations/min)",HIB,2158,2143,2126,2141 "Timed Wasmer Compilation - Time To Compile (sec)",LIB,51.506,50.784,51.03,51.238 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,13.19,13.07,13.12,13.03 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,514182,508103,512426,508007 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,3601.88,3627.02,3587.71,3607.68 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,17.67,17.57,17.74,17.66 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,1389.97,1384.14,1378.82,1382.59 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,45.76,45.84,46.11,46 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,1812.71,1819.02,1809.47,1805.61 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,35.26,35.14,35.33,35.4 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,1895.81,1898.11,1899.96,1908.3 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,33.72,33.68,33.64,33.5 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,4753.02,4783.65,4759.67,4783.28 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,13.03,13.04,12.97,13.01 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,217.19,216.22,217.36,217.05 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,294.05,295.39,293.88,294.37 "Timed CPython Compilation - Build Configuration: Released Build, PGO + LTO Optimized (sec)",LIB,261.72,260.978,261.764,262.072 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,4799.15,4791.04,4797.26,4809.55 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,2937.36,2935.11,2935.22,2927.35 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,21.76,21.77,21.77,21.83 "Timed CPython Compilation - Build Configuration: Default (sec)",LIB,15.304,15.263,15.296,15.275 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,3117.18,3121.06,3123.56,3118.52 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,20.51,20.48,20.47,20.5 "Timed PHP Compilation - Time To Compile (sec)",LIB,39.09,39.118,39.164,39.102 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,28.11,28.09,28.08,28.09 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,4550.37,4553.62,4554.06,4553.16