9654 new
2 x AMD EPYC 9654 96-Core testing with a AMD Titanite_4G (RTI1004D BIOS) and llvmpipe on Red Hat Enterprise Linux 9.1 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2303114-NE-9654NEW5019&grt&sro.
ClickHouse
100M Rows Hits Dataset, First Run / Cold Cache
ClickHouse
100M Rows Hits Dataset, Second Run
ClickHouse
100M Rows Hits Dataset, Third Run
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Slow
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Medium
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Slow
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Medium
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Very Fast
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Super Fast
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Very Fast
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Super Fast
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
Memcached
Set To Get Ratio: 1:5
Memcached
Set To Get Ratio: 1:10
Memcached
Set To Get Ratio: 1:100
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-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
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
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
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: 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: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
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: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
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
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVKL
Benchmark: vklBenchmark ISPC
OpenVKL
Benchmark: vklBenchmark Scalar
RocksDB
Test: Random Fill
RocksDB
Test: Random Read
RocksDB
Test: Update Random
RocksDB
Test: Sequential Fill
RocksDB
Test: Random Fill Sync
RocksDB
Test: Read While Writing
RocksDB
Test: Read Random Write Random
Stress-NG
Test: Hash
Stress-NG
Test: MMAP
Stress-NG
Test: NUMA
Stress-NG
Test: Poll
Stress-NG
Test: Futex
Stress-NG
Test: MEMFD
Stress-NG
Test: Mutex
Stress-NG
Test: Atomic
Stress-NG
Test: Crypto
Stress-NG
Test: Malloc
Stress-NG
Test: Forking
Stress-NG
Test: Pthread
Stress-NG
Test: SENDFILE
Stress-NG
Test: CPU Cache
Stress-NG
Test: CPU Stress
Stress-NG
Test: Semaphores
Stress-NG
Test: Matrix Math
Stress-NG
Test: Vector Math
Stress-NG
Test: Function Call
Stress-NG
Test: Memory Copying
Stress-NG
Test: Socket Activity
Stress-NG
Test: Context Switching
Stress-NG
Test: Glibc C String Functions
Stress-NG
Test: Glibc Qsort Data Sorting
Stress-NG
Test: System V Message Passing
Timed FFmpeg Compilation
Time To Compile
Timed Linux Kernel Compilation
Build: defconfig
uvg266
Video Input: Bosphorus 4K - Video Preset: Slow
uvg266
Video Input: Bosphorus 4K - Video Preset: Medium
uvg266
Video Input: Bosphorus 1080p - Video Preset: Slow
uvg266
Video Input: Bosphorus 1080p - Video Preset: Medium
uvg266
Video Input: Bosphorus 4K - Video Preset: Very Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Super Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Very Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Super Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
VP9 libvpx Encoding
Speed: Speed 0 - Input: Bosphorus 4K
VP9 libvpx Encoding
Speed: Speed 5 - Input: Bosphorus 4K
VP9 libvpx Encoding
Speed: Speed 0 - Input: Bosphorus 1080p
VP9 libvpx Encoding
Speed: Speed 5 - Input: Bosphorus 1080p
VVenC
Video Input: Bosphorus 4K - Video Preset: Fast
VVenC
Video Input: Bosphorus 4K - Video Preset: Faster
VVenC
Video Input: Bosphorus 1080p - Video Preset: Fast
VVenC
Video Input: Bosphorus 1080p - Video Preset: Faster
Zstd Compression
Compression Level: 3 - Compression Speed
Zstd Compression
Compression Level: 3 - Decompression Speed
Zstd Compression
Compression Level: 8 - Compression Speed
Zstd Compression
Compression Level: 8 - Decompression Speed
Zstd Compression
Compression Level: 12 - Compression Speed
Zstd Compression
Compression Level: 12 - Decompression Speed
Zstd Compression
Compression Level: 19 - Compression Speed
Zstd Compression
Compression Level: 19 - Decompression Speed
Zstd Compression
Compression Level: 3, Long Mode - Compression Speed
Zstd Compression
Compression Level: 3, Long Mode - Decompression Speed
Zstd Compression
Compression Level: 8, Long Mode - Compression Speed
Zstd Compression
Compression Level: 8, Long Mode - Decompression Speed
Zstd Compression
Compression Level: 19, Long Mode - Compression Speed
Zstd Compression
Compression Level: 19, Long Mode - Decompression Speed
Phoronix Test Suite v10.8.5