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AMD EPYC 8534PN 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/2401085-NE-DDF90911740&rdt&grs.
LeelaChessZero
Backend: BLAS
WebP2 Image Encode
Encode Settings: Quality 75, Compression Effort 7
Timed Gem5 Compilation
Time To Compile
LeelaChessZero
Backend: Eigen
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 4K
WebP2 Image Encode
Encode Settings: Quality 95, Compression Effort 7
QuantLib
Configuration: Multi-Threaded
PyTorch
Device: CPU - Batch Size: 16 - Model: ResNet-152
CloverLeaf
Input: clover_bm
Xmrig
Variant: CryptoNight-Heavy - Hash Count: 1M
Speedb
Test: Update Random
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
OpenRadioss
Model: Rubber O-Ring Seal Installation
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
Speedb
Test: Random Fill Sync
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
WebP2 Image Encode
Encode Settings: Default
PyTorch
Device: CPU - Batch Size: 64 - Model: ResNet-152
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
PyTorch
Device: CPU - Batch Size: 32 - Model: ResNet-152
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
PyTorch
Device: CPU - Batch Size: 64 - Model: ResNet-50
OpenRadioss
Model: Bumper Beam
Embree
Binary: Pathtracer - Model: Crown
Speedb
Test: Read While Writing
OpenRadioss
Model: Bird Strike on Windshield
Embree
Binary: Pathtracer ISPC - Model: Crown
FFmpeg
Encoder: libx265 - Scenario: Live
PyTorch
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
rav1e
Speed: 6
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
PyTorch
Device: CPU - Batch Size: 32 - Model: ResNet-50
OpenRadioss
Model: INIVOL and Fluid Structure Interaction Drop Container
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
Speedb
Test: Sequential Fill
Embree
Binary: Pathtracer - Model: Asian Dragon Obj
Blender
Blend File: Classroom - Compute: CPU-Only
PyTorch
Device: CPU - Batch Size: 16 - Model: ResNet-50
Blender
Blend File: Fishy Cat - Compute: CPU-Only
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Timed FFmpeg Compilation
Time To Compile
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream
TensorFlow
Device: CPU - Batch Size: 16 - Model: ResNet-50
PyTorch
Device: CPU - Batch Size: 1 - Model: ResNet-50
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
OpenRadioss
Model: Chrysler Neon 1M
Xmrig
Variant: Wownero - Hash Count: 1M
TensorFlow
Device: CPU - Batch Size: 16 - Model: AlexNet
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Quicksilver
Input: CTS2
WebP2 Image Encode
Encode Settings: Quality 100, Compression Effort 5
Y-Cruncher
Pi Digits To Calculate: 1B
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
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
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200
FFmpeg
Encoder: libx265 - Scenario: Upload
Speedb
Test: Random Fill
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
rav1e
Speed: 5
PyTorch
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
PyTorch
Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l
Quicksilver
Input: CORAL2 P1
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
rav1e
Speed: 10
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
OpenRadioss
Model: Cell Phone Drop Test
Xmrig
Variant: CryptoNight-Femto UPX2 - Hash Count: 1M
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Xmrig
Variant: GhostRider - Hash Count: 1M
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Xmrig
Variant: KawPow - Hash Count: 1M
PyTorch
Device: CPU - Batch Size: 1 - Model: ResNet-152
Y-Cruncher
Pi Digits To Calculate: 10B
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
CloverLeaf
Input: clover_bm64_short
Embree
Binary: Pathtracer - Model: Asian Dragon
TensorFlow
Device: CPU - Batch Size: 16 - Model: VGG-16
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
FFmpeg
Encoder: libx265 - Scenario: Video On Demand
FFmpeg
Encoder: libx265 - Scenario: Platform
Blender
Blend File: BMW27 - Compute: CPU-Only
Y-Cruncher
Pi Digits To Calculate: 5B
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Quicksilver
Input: CORAL2 P2
Blender
Blend File: Barbershop - Compute: CPU-Only
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
QuantLib
Configuration: Single-Threaded
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Speedb
Test: Random Read
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: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Xmrig
Variant: Monero - Hash Count: 1M
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Y-Cruncher
Pi Digits To Calculate: 500M
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
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
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
TensorFlow
Device: CPU - Batch Size: 1 - Model: AlexNet
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Blender
Blend File: Pabellon Barcelona - Compute: CPU-Only
Speedb
Test: Read Random Write Random
TensorFlow
Device: CPU - Batch Size: 16 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 1 - Model: ResNet-50
TensorFlow
Device: CPU - Batch Size: 1 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 1 - Model: VGG-16
PyTorch
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
rav1e
Speed: 1
WebP2 Image Encode
Encode Settings: Quality 100, Lossless Compression
Phoronix Test Suite v10.8.5