AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 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 2403160-NE-KDLKF039836
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