Tests for a future article. 2 x Intel Xeon Platinum 8280 testing with a GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS) and ASPEED on Ubuntu 21.04 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 2301061-NE-XEONPLATI67
xeon platinum 8280 2023
Tests for a future article. 2 x Intel Xeon Platinum 8280 testing with a GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS) and ASPEED on Ubuntu 21.04 via the Phoronix Test Suite.
,,"a","b"
Processor,,2 x Intel Xeon Platinum 8280 @ 4.00GHz (56 Cores / 112 Threads),2 x Intel Xeon Platinum 8280 @ 4.00GHz (56 Cores / 112 Threads)
Motherboard,,GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS),GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS)
Chipset,,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers
Memory,,384GB,384GB
Disk,,280GB INTEL SSDPED1D280GA,280GB INTEL SSDPED1D280GA
Graphics,,ASPEED,ASPEED
Monitor,,VE228,VE228
Network,,2 x Intel X722 for 1GbE + 2 x QLogic FastLinQ QL41000 10/25/40/50GbE,2 x Intel X722 for 1GbE + 2 x QLogic FastLinQ QL41000 10/25/40/50GbE
OS,,Ubuntu 21.04,Ubuntu 21.04
Kernel,,5.11.0-49-generic (x86_64),5.11.0-49-generic (x86_64)
Desktop,,GNOME Shell 3.38.4,GNOME Shell 3.38.4
Display Server,,X Server,X Server
Compiler,,GCC 10.3.0,GCC 10.3.0
File-System,,ext4,ext4
Screen Resolution,,1920x1080,1920x1080
,,"a","b"
"BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,405341,401379
"OpenVKL - Benchmark: vklBenchmark Scalar (Items / Sec)",HIB,255,253
"OpenVKL - Benchmark: vklBenchmark ISPC (Items / Sec)",HIB,520,522
"PostgreSQL - Scaling Factor: 1 - Clients: 1000 - Mode: Read Write - Average Latency (ms)",LIB,4233.601,4274.622
"PostgreSQL - Scaling Factor: 1 - Clients: 1000 - Mode: Read Write (TPS)",HIB,236,234
"PostgreSQL - Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency (ms)",LIB,2868.828,3073.441
"PostgreSQL - Scaling Factor: 1 - Clients: 800 - Mode: Read Write (TPS)",HIB,279,260
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency (ms)",LIB,19.742,19.855
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Write (TPS)",HIB,50653,50366
"PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency (ms)",LIB,0.067,0.066
"PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Only (TPS)",HIB,1499937,1509915
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency (ms)",LIB,0.61,0.573
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Only (TPS)",HIB,1638286,1745701
"PostgreSQL - Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency (ms)",LIB,3.857,3.81
"PostgreSQL - Scaling Factor: 100 - Clients: 250 - Mode: Read Write (TPS)",HIB,64820,65615
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency (ms)",LIB,14.318,14.306
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Write (TPS)",HIB,55873,55920
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency (ms)",LIB,0.449,0.469
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Only (TPS)",HIB,1783440,1707442
"PostgreSQL - Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency (ms)",LIB,7.938,7.939
"PostgreSQL - Scaling Factor: 100 - Clients: 500 - Mode: Read Write (TPS)",HIB,62985,62982
"PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency (ms)",LIB,1.703,1.702
"PostgreSQL - Scaling Factor: 100 - Clients: 100 - Mode: Read Write (TPS)",HIB,58725,58760
"PostgreSQL - Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency (ms)",LIB,0.277,0.277
"PostgreSQL - Scaling Factor: 100 - Clients: 500 - Mode: Read Only (TPS)",HIB,1802196,1805423
"PostgreSQL - Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency (ms)",LIB,0.14,0.139
"PostgreSQL - Scaling Factor: 100 - Clients: 250 - Mode: Read Only (TPS)",HIB,1785647,1793551
"PostgreSQL - Scaling Factor: 1 - Clients: 500 - Mode: Read Write - Average Latency (ms)",LIB,1366.382,2089.942
"PostgreSQL - Scaling Factor: 1 - Clients: 500 - Mode: Read Write (TPS)",HIB,366,239
"PostgreSQL - Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency (ms)",LIB,332.488,350.08
"PostgreSQL - Scaling Factor: 1 - Clients: 250 - Mode: Read Write (TPS)",HIB,752,714
"PostgreSQL - Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency (ms)",LIB,0.448,0.466
"PostgreSQL - Scaling Factor: 1 - Clients: 800 - Mode: Read Only (TPS)",HIB,1787570,1715536
"PostgreSQL - Scaling Factor: 1 - Clients: 500 - Mode: Read Only - Average Latency (ms)",LIB,0.284,0.276
"PostgreSQL - Scaling Factor: 1 - Clients: 500 - Mode: Read Only (TPS)",HIB,1759394,1809420
"PostgreSQL - Scaling Factor: 1 - Clients: 1000 - Mode: Read Only - Average Latency (ms)",LIB,0.56,0.606
"PostgreSQL - Scaling Factor: 1 - Clients: 1000 - Mode: Read Only (TPS)",HIB,1785534,1651399
"PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency (ms)",LIB,73.247,73.369
"PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Write (TPS)",HIB,1365,1363
"PostgreSQL - Scaling Factor: 1 - Clients: 250 - Mode: Read Only - Average Latency (ms)",LIB,0.148,0.139
"PostgreSQL - Scaling Factor: 1 - Clients: 250 - Mode: Read Only (TPS)",HIB,1690140,1795519
"PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency (ms)",LIB,0.064,0.063
"PostgreSQL - Scaling Factor: 1 - Clients: 100 - Mode: Read Only (TPS)",HIB,1564863,1584160
"CockroachDB - Workload: KV, 10% Reads - Concurrency: 1024 (ops/s)",HIB,65744.1,63330.8
"CockroachDB - Workload: KV, 50% Reads - Concurrency: 1024 (ops/s)",HIB,82225.7,73573.9
"CockroachDB - Workload: KV, 60% Reads - Concurrency: 1024 (ops/s)",HIB,86582.7,85611.1
"CockroachDB - Workload: KV, 95% Reads - Concurrency: 1024 (ops/s)",HIB,101568.6,94955.4
"CockroachDB - Workload: KV, 10% Reads - Concurrency: 512 (ops/s)",HIB,67125.8,66853.5
"CockroachDB - Workload: KV, 60% Reads - Concurrency: 512 (ops/s)",HIB,90837.1,89886.1
"CockroachDB - Workload: KV, 50% Reads - Concurrency: 512 (ops/s)",HIB,76437.2,84220
"CockroachDB - Workload: KV, 95% Reads - Concurrency: 512 (ops/s)",HIB,101544,91775.4
"CockroachDB - Workload: KV, 10% Reads - Concurrency: 256 (ops/s)",HIB,67990,68326.9
"CockroachDB - Workload: KV, 60% Reads - Concurrency: 256 (ops/s)",HIB,86044.5,84529.4
"CockroachDB - Workload: KV, 50% Reads - Concurrency: 256 (ops/s)",HIB,81102.6,89629.3
"CockroachDB - Workload: KV, 95% Reads - Concurrency: 256 (ops/s)",HIB,98761.4,99967.9
"CockroachDB - Workload: KV, 50% Reads - Concurrency: 128 (ops/s)",HIB,80437.3,85022.7
"CockroachDB - Workload: KV, 60% Reads - Concurrency: 128 (ops/s)",HIB,85674,91688.8
"CockroachDB - Workload: KV, 10% Reads - Concurrency: 128 (ops/s)",HIB,65449.2,66632.8
"CockroachDB - Workload: KV, 95% Reads - Concurrency: 128 (ops/s)",HIB,110812.8,99710
"CockroachDB - Workload: MoVR - Concurrency: 1024 (ops/s)",HIB,360,366.9
"CockroachDB - Workload: MoVR - Concurrency: 128 (ops/s)",HIB,380,358.2
"CockroachDB - Workload: MoVR - Concurrency: 512 (ops/s)",HIB,381.8,391.7
"CockroachDB - Workload: MoVR - Concurrency: 256 (ops/s)",HIB,400.6,365.6
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,876.576,877.97
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,875.659,878.287
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,876.443,890.453
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,467.099,460.988
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,463.667,453.862
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,457.84,458.51
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Slow (FPS)",HIB,7.71,7.69
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Medium (FPS)",HIB,8.4,8.46
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Slow (FPS)",HIB,8.82,8.87
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,1407.71,1404.1
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,9.85,9.89
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Medium (FPS)",HIB,9.06,9.08
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,1429.13,1430.6
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,9.73,9.7
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,753.02,754.14
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,18.52,18.46
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,201.21,200.93
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,69.52,69.6
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,74.75,74.85
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,187.05,186.77
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,8.07,8.05
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,6929.07,6948.2
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,30.67,30.59
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,1819.1,1824.35
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,10.81,10.83
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,1289.59,1286.83
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,1.03,1.03
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,53593.95,53495.65
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,1.15,1.15
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,48267.15,48001.2
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,4.82,4.82
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,2888.87,2889.46
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,20.45,20.78
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,682.54,672.12
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Very Fast (FPS)",HIB,17.02,16.99
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Very Fast (FPS)",HIB,18.86,18.75
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Ultra Fast (FPS)",HIB,21.65,21.03
"uvg266 - Video Input: Bosphorus 4K - Video Preset: Super Fast (FPS)",HIB,22.08,22.03
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Super Fast (FPS)",HIB,22.36,22.48
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Slow (FPS)",HIB,23.33,23.69
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Medium (FPS)",HIB,25.25,25.28
"Kvazaar - Video Input: Bosphorus 4K - Video Preset: Ultra Fast (FPS)",HIB,25.91,25.98
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,18.6138,18.5701
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,4.84062,4.8545
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.434424,0.43882
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Slow (FPS)",HIB,33.06,33.25
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Medium (FPS)",HIB,34.2,33.56
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,1.30989,1.29942
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3.71301,3.69864
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.39001,1.40389
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2.45477,2.27592
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,0.327524,0.329008
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.194345,0.199945
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Very Fast (FPS)",HIB,59.51,59.8
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,3.00282,3.02197
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2.10746,2.11619
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.08776,1.13263
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Super Fast (FPS)",HIB,68.3,67.77
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Very Fast (FPS)",HIB,73.05,69.55
"uvg266 - Video Input: Bosphorus 1080p - Video Preset: Ultra Fast (FPS)",HIB,79.04,79.21
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,3.93265,3.88472
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.64132,3.62224
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Super Fast (FPS)",HIB,97.08,94.9
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3.14259,3.13757
"Kvazaar - Video Input: Bosphorus 1080p - Video Preset: Ultra Fast (FPS)",HIB,119.74,118.28
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,4.43676,4.4349
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,1.21248,1.21791
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.331943,0.336858