kdlkf

AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

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C/C++ Compiler Tests 2 Tests
CPU Massive 7 Tests
Creator Workloads 8 Tests
Encoding 2 Tests
HPC - High Performance Computing 3 Tests
Imaging 2 Tests
Machine Learning 3 Tests
Multi-Core 8 Tests
Intel oneAPI 2 Tests
Python Tests 2 Tests
Server CPU Tests 4 Tests

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a
March 16
  1 Hour, 35 Minutes
b
March 16
  1 Hour, 35 Minutes
c
March 17
  1 Hour, 35 Minutes
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kdlkf AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite. ,,"a","b","c" Processor,,AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads),AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads),AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads) Motherboard,,AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS) Chipset,,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4 Memory,,6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG Disk,,3201GB Micron_7450_MTFDKCB3T2TFS,3201GB Micron_7450_MTFDKCB3T2TFS,3201GB Micron_7450_MTFDKCB3T2TFS Graphics,,ASPEED,ASPEED,ASPEED Network,,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe OS,,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10 Kernel,,6.5.0-15-generic (x86_64),6.5.0-15-generic (x86_64),6.5.0-15-generic (x86_64) Desktop,,GNOME Shell,GNOME Shell,GNOME Shell Display Server,,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7 Compiler,,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0 File-System,,ext4,ext4,ext4 Screen Resolution,,1920x1200,1920x1200,1920x1200 ,,"a","b","c" "Chaos Group V-RAY - Mode: CPU (vsamples)",HIB,92008,92099,91007 "Google Draco - Model: Lion (ms)",LIB,6301,6258,6255 "Google Draco - Model: Church Facade (ms)",LIB,8195,8069,8162 "JPEG-XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,49.659,49.682,49.75 "JPEG-XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,551.294,546.955,536.436 "JPEG-XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,42.814,40.411,45.024 "JPEG-XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,36.939,41.748,37.525 "JPEG-XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,40.431,43.883,40.657 "JPEG-XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,39.591,38.181,38.066 "JPEG-XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,29.416,29.496,29.554 "JPEG-XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,30.194,30.026,29.923 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,35.617,35.7366,35.6174 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,881.713,883.0605,883.404 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,29.7164,29.7149,29.7235 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,33.6419,33.6426,33.6331 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1442.7872,1439.2863,1440.7025 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,22.147,22.2042,22.183 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,202.1044,203.9295,201.0406 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,4.9422,4.8985,4.9685 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,476.8285,476.8142,476.8799 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,66.9939,66.9855,67.0359 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (items/sec)",HIB,187.2838,187.1998,187.4636 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.3331,5.3354,5.3276 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3769.7196,3790.7984,3797.2428 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,8.4671,8.4216,8.4068 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,823.7786,820.597,796.3509 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,1.2101,1.2147,1.2517 "Neural Magic DeepSparse - Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2.8545,2.8315,2.8225 "Neural Magic DeepSparse - Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,9727.6824,9786.0632,9824.214 "Neural Magic DeepSparse - Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream (items/sec)",HIB,14.3821,14.3538,14.3578 "Neural Magic DeepSparse - Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream (ms/batch)",LIB,69.4979,69.6373,69.6194 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,477.048,476.5308,476.8231 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,66.9654,67.0123,66.9884 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,186.9693,186.9956,186.6661 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.3423,5.3412,5.3508 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,213.9443,212.4733,213.196 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,149.2455,150.0741,149.6143 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,154.5035,154.039,154.4093 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,6.4656,6.4846,6.4692 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,314.4659,315.2865,314.4763 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,101.5303,101.3076,101.6256 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,136.9731,137.7834,138.0557 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,7.2927,7.2496,7.2356 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,62.3522,62.2981,62.3947 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,509.3081,508.6027,507.7182 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (items/sec)",HIB,44.1116,44.0724,44.058 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (ms/batch)",LIB,22.645,22.6651,22.671 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,685.2338,686.678,683.7678 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,46.624,46.5298,46.7235 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,64.4883,64.4166,64.008 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,15.4906,15.5082,15.6061 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,35.7614,35.5936,35.6837 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,882.3366,883.107,882.8675 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,29.7516,29.742,29.7584 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,33.6018,33.6124,33.5952 "oneDNN - Harness: IP Shapes 1D - Engine: CPU (ms)",LIB,0.796392,0.791773,0.802263 "oneDNN - Harness: IP Shapes 3D - Engine: CPU (ms)",LIB,0.990182,0.992488,0.9919 "oneDNN - Harness: Convolution Batch Shapes Auto - Engine: CPU (ms)",LIB,1.18235,1.18126,1.17292 "oneDNN - Harness: Deconvolution Batch shapes_1d - Engine: CPU (ms)",LIB,8.73308,8.78255,8.75546 "oneDNN - Harness: Deconvolution Batch shapes_3d - Engine: CPU (ms)",LIB,1.45255,1.45945,1.45433 "oneDNN - Harness: Recurrent Neural Network Training - Engine: CPU (ms)",LIB,746.673,752.481,745.409 "oneDNN - Harness: Recurrent Neural Network Inference - Engine: CPU (ms)",LIB,455.016,457.825,457.713 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,29.64,29.59,29.6 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,1077.23,1076.61,1076.35 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,217.12,216.75,216.84 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,147.21,147.48,147.42 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,216.99,217.07,216.93 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,147.33,147.26,147.35 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,1332.49,1330.83,1332.74 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,23.96,23.99,23.96 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,56.39,56.45,56.51 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,564.47,564.47,564.32 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,6930.15,6920.51,6927.9 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,4.6,4.61,4.6 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,556.51,546.67,545.93 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,57.43,58.46,58.54 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,3015.55,2988.49,3012.81 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,10.59,10.69,10.6 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,2966.79,2968.32,2969.13 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,21.55,21.54,21.53 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,9773.24,9793.26,9779.93 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,6.53,6.52,6.53 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,1051.9,1054.53,1049.11 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,30.38,30.3,30.46 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,331.17,331.65,331.63 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,96.5,96.35,96.38 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,5678.12,5685.06,5681.48 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,11.26,11.24,11.25 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,2974.2,2945.11,2934.13 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,10.73,10.84,10.88 "OpenVINO - Model: Noise Suppression Poconet-Like FP16 - Device: CPU (FPS)",HIB,3817.87,3825.64,3828.3 "OpenVINO - Model: Noise Suppression Poconet-Like FP16 - Device: CPU (ms)",LIB,16.53,16.51,16.49 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,1541.43,1540,1525.91 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,41.49,41.53,41.91 "OpenVINO - Model: Person Re-Identification Retail FP16 - Device: CPU (FPS)",HIB,3927.6,3916.92,3921.98 "OpenVINO - Model: Person Re-Identification Retail FP16 - Device: CPU (ms)",LIB,8.13,8.15,8.14 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,68063.14,68303.49,68152.88 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.77,0.77,0.77 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,1616.79,1621.11,1621.25 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,39.55,39.45,39.45 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,86126.49,86415.41,85841.12 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.58,0.58,0.58 "Parallel BZIP2 Compression - FreeBSD-13.0-RELEASE-amd64-memstick.img Compression (sec)",LIB,2.016558,2.170377,2.05767 "Primesieve - Length: 1e12 (sec)",LIB,3.556,3.554,3.531 "Primesieve - Length: 1e13 (sec)",LIB,42.899,42.76,42.843 "srsRAN Project - Test: PDSCH Processor Benchmark, Throughput Total (Mbps)",HIB,21012.2,21055.5,20479.7 "srsRAN Project - Test: PDSCH Processor Benchmark, Throughput Thread (Mbps)",HIB,545.7,628.9,630.9 "Stockfish - Chess Benchmark (Nodes/s)",HIB,98973914,110763828,97292518 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,7,7.005,6.925 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,71.236,68.579,69.504 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,165.278,165.007,165.215 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,167.56,166.211,165.244 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,18.754,18.76,19.067 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,142.846,142.252,145.058 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,507.358,499.827,509.752 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,577.697,582.509,565.037 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,44.295,44.409,44.392 "Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,391.242,391.934,391.027 "WavPack Audio Encoding - WAV To WavPack (sec)",LIB,6.067,6.066,6.059