Tests for a future article. 2 x AMD EPYC 7303 16-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 2310231-NE-77132P99738
7713 2P
Tests for a future article. 2 x AMD EPYC 7303 16-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.
,,"a","b","c","AMD EPYC 7303 16-Core","d","e","f","g"
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),AMD EPYC 7303 16-Core @ 2.40GHz (16 Cores / 32 Threads),2 x AMD EPYC 7203 8-Core @ 2.80GHz (16 Cores / 32 Threads),2 x AMD EPYC 7303 16-Core @ 2.40GHz (32 Cores / 64 Threads),2 x AMD EPYC 7303 16-Core @ 2.40GHz (32 Cores / 64 Threads),2 x AMD EPYC 7303 16-Core @ 2.40GHz (32 Cores / 64 Threads)
Motherboard,,AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),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,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse,AMD Starship/Matisse
Memory,,256GB,256GB,256GB,256GB,512GB,512GB,512GB,512GB
Disk,,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP
Graphics,,ASPEED,ASPEED,ASPEED,ASPEED,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 MT27710,2 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,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04
Kernel,,5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64),5.15.0-47-generic (x86_64)
Desktop,,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,GNOME Shell 42.4,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,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,,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204,1.2.204
Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0
File-System,,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080,1920x1080,1024x768,1024x768,1024x768,1024x768
,,"a","b","c","AMD EPYC 7303 16-Core","d","e","f","g"
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,9543.23,9544.95,9527.76,1754.67,1232.95,3153.9,3148.82,3148.97
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,2687.19,2655.09,2694.27,520.89,369.7,873.34,865.28,875.64
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,3308.28,3302.83,3303.59,570.58,470.46,1096.25,1095.27,1095.68
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,1342.68,1340.29,1340.12,237.79,195.5,415.32,415.12,415.15
"Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,153.78,152.94,152.5,871.17,974.94,505.43,504.18,506.55
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,643823,647995,678765,116102,106826,214511,216258,218417
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,5333.24,5334.87,5335.15,858.21,856.63,1727.34,1708.45,1725.37
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,51.12,51.17,51.2,8.66,8.35,17.2,17.27,17.28
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,49.66,49.32,48.96,280.03,296.74,155.52,157.08,157.59
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,40.28,40.21,40.04,226.06,237.87,116.68,117.05,118.34
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,16.08,16.08,16.19,89.45,94.86,50.21,50.25,50.09
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,899.15,897.77,898.69,155.5,171.61,303.8,303.83,303.59
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,20.44,20.73,20.45,109.21,116.66,62.52,62.18,62.31
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,202.68,203.14,203.96,42.11,37.06,72.71,73.23,72.14
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,226.15,226.27,222.73,47.46,43.18,85.51,85.46,84.86
"Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,182.491,179.986,179.539,815.395,830.492,462.138,462.599,462.696
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,507611,505036,499347,135892,113384,210620,212139,209887
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,98494.41,101883.13,101985.21,23110.2,23725.57,46823.73,45126.45,47926.34
"Remhos - Test: Sample Remap Example (sec)",LIB,11.284,11.02,11.709,37.307,39.71,23.463,23.488,23.723
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,132.37,129.61,132.8,357.27,429.22,302.03,305.55,307.24
"OpenRadioss - Model: Chrysler Neon 1M (sec)",LIB,174.49,173.59,174.45,551.24,489.75,304.03,306.37,303.58
"Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,23.875,23.974,23.939,67.408,68.675,43.41,43.477,43.318
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,26.54,26.35,26.53,65.55,63.71,41.05,41.01,40.85
"libxsmm - M N K: 64 (GFLOPS/s)",HIB,980.5,923.9,920.8,406.9,442.5,727.2,737.3,723.4
"Laghos - Test: Sedov Blast Wave, ube_922_hex.mesh (Major Kernels Rate)",HIB,282.55,282.08,279.20,148.49,132.46,234.135345612,233.54,233.047063651
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,623.9,623.64,623.6,921.14,478.92,463.57,462.78,462.57
"libxsmm - M N K: 32 (GFLOPS/s)",HIB,540.3,471,467.3,273.2,356.5,484.7,482.9,470.9
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,9.66,9.68,9.67,14,8.49,7.29,7.29,7.29
"OpenVKL - Benchmark: vklBenchmarkCPU Scalar (Items / Sec)",HIB,,,,,144,273,275,274
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,,,,,15.8702,29.9805,30.1314,30.0261
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,,,,,13.8445,26.0698,26.2737,26.1574
"Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,,,,,17.4784,32.9696,33.0392,32.9662
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,,,,,16.1253,30.1028,30.3378,30.2552
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,,,,,15.7439,29.6195,29.5206,29.5908
"OpenVKL - Benchmark: vklBenchmarkCPU ISPC (Items / Sec)",HIB,,,,,267,495,497,495
"Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,,,,,14.3991,26.5233,26.6112,26.3986
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,141.33,141.24,143.55,168.3,92.53,93.45,93.5,94.17
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,3.34,3.34,3.35,4.55,3.24,2.53,2.53,2.53
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,3.248,3.331,3.309,5.282,5.771,3.965,3.976,3.962
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,157.75,157.4,156.74,189.92,107.81,109.89,109.16,110.71
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,23.81,23.85,23.86,33.62,20.44,19.25,19.25,19.25
"Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,,,,,0.28,0.48,0.48,0.48
"Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,,,,,0.56,0.95,0.95,0.95
"Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,,,,,0.56,0.95,0.95,0.95
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,11.89,12.03,11.86,15.34,10.8,9.13,9.21,9.11
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,75.603,75.778,75.836,120.85,125.918,92.447,91.913,92.528
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,1.92811,1.16856,1.16545,1.17023
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,147.64,146.17,146.31,202.93,235.98,192.24,192.62,192.49
"Laghos - Test: Triple Point Problem (Major Kernels Rate)",HIB,164.19,162.65,167.28,132.65,114.18,182.23,181.55,180.93
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,1.6509,1.44749,1.92348,2.28469
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,2.67723,1.74244,1.69817,1.84652
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,41.424,40.837,42.41,60.19,64.146,48.724,48.844,48.731
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,142.22,142.42,142.29,102.82,93.16,105.22,105.23,105.33
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,4.63185,3.14371,3.06111,3.14105
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,6.786,6.881,6.929,9.186,10.133,7.801,7.824,7.825
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,0.768449,1.05324,1.14379,1.08661
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,2.34565,1.89405,1.77064,2.1207
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,130.4,134.61,131.25,102.8,129.36,118.07,120.33,122.81
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.85,0.85,0.86,0.68,0.66,0.67,0.7,0.66
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,1451.2,1114.67,1139.54,1129.54
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,1466.25,1137.11,1128.3,1149.15
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,23.98,23.98,23.97,18.63,18.65,18.46,18.67,18.48
"OpenRadioss - Model: Bumper Beam (sec)",LIB,115.89,116.73,116.3,118.33,134.32,105.44,105.68,107.04
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,1445.86,1161.8,1153.45,1145.62
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 (sec)",LIB,,,,,3.291,2.831,2.672,2.766
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 (sec)",LIB,,,,,65.733,55.336,60.049,56.337
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,4.51333,3.84916,4.18974,3.94733
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,3037.72,3379.25,3281.24,3556.44
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,3019.31,3494.51,3341.93,3451.09
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 (sec)",LIB,,,,,149.203,140.297,130.447,133.177
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,3028.36,3216.13,3462.9,3272.36
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,5.474,5.485,5.535,5.779,6.186,5.855,5.817,5.815
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,4.27338,4.10412,3.83995,4.05768
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,,,,,5.54136,5.67018,5.66435,5.63319
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,,,,,1.94173,1.93352,1.9522,1.95024
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,,,,
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,,,,
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,,,,
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,,,,
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,,,,,,