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AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403160-NE-KDLKF039836&grs.
srsRAN Project
Test: PDSCH Processor Benchmark, Throughput Thread
Stockfish
Chess Benchmark
JPEG-XL libjxl
Input: PNG - Quality: 90
JPEG-XL libjxl
Input: PNG - Quality: 80
JPEG-XL libjxl
Input: JPEG - Quality: 80
Parallel BZIP2 Compression
FreeBSD-13.0-RELEASE-amd64-memstick.img Compression
JPEG-XL libjxl
Input: JPEG - Quality: 90
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
srsRAN Project
Test: PDSCH Processor Benchmark, Throughput Total
JPEG-XL Decoding libjxl
CPU Threads: All
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
OpenVINO
Model: Road Segmentation ADAS FP16 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16 - Device: CPU
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
Google Draco
Model: Church Facade
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 4K
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
oneDNN
Harness: IP Shapes 1D - Engine: CPU
Chaos Group V-RAY
Mode: CPU
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Handwritten English Recognition FP16 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16 - Device: CPU
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream
oneDNN
Harness: Recurrent Neural Network Training - Engine: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
JPEG-XL libjxl
Input: JPEG - Quality: 100
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Engine: CPU
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Google Draco
Model: Lion
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Primesieve
Length: 1e12
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Engine: CPU
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Engine: CPU
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
JPEG-XL libjxl
Input: PNG - Quality: 100
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Primesieve
Length: 1e13
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
OpenVINO
Model: Person Re-Identification Retail FP16 - Device: CPU
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Timed Linux Kernel Compilation
Build: defconfig
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Person Re-Identification Retail FP16 - Device: CPU
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
oneDNN
Harness: IP Shapes 3D - Engine: CPU
Timed Linux Kernel Compilation
Build: allmodconfig
OpenVINO
Model: Face Detection Retail FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16-INT8 - Device: CPU
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Person Detection FP16 - Device: CPU
JPEG-XL Decoding libjxl
CPU Threads: 1
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Face Detection Retail FP16-INT8 - Device: CPU
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
OpenVINO
Model: Face Detection Retail FP16 - Device: CPU
WavPack Audio Encoding
WAV To WavPack
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
Phoronix Test Suite v10.8.5