eptc-7f32
AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 11 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2211207-NE-EPTC7F32776&grr.
TensorFlow
Device: CPU - Batch Size: 256 - Model: ResNet-50
WebP2 Image Encode
Encode Settings: Quality 100, Lossless Compression
BRL-CAD
VGR Performance Metric
TensorFlow
Device: CPU - Batch Size: 256 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 512 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 64 - Model: ResNet-50
OpenRadioss
Model: INIVOL and Fluid Structure Interaction Drop Container
Timed Node.js Compilation
Time To Compile
SMHasher
Hash: SHA3-256
SMHasher
Hash: SHA3-256
miniBUDE
Implementation: OpenMP - Input Deck: BM2
miniBUDE
Implementation: OpenMP - Input Deck: BM2
WebP2 Image Encode
Encode Settings: Quality 95, Compression Effort 7
JPEG XL libjxl
Input: JPEG - Quality: 100
JPEG XL libjxl
Input: PNG - Quality: 100
TensorFlow
Device: CPU - Batch Size: 32 - Model: ResNet-50
TensorFlow
Device: CPU - Batch Size: 256 - Model: AlexNet
Timed CPython Compilation
Build Configuration: Released Build, PGO + LTO Optimized
OpenRadioss
Model: Bird Strike on Windshield
FFmpeg
Encoder: libx264 - Scenario: Upload
FFmpeg
Encoder: libx264 - Scenario: Upload
FFmpeg
Encoder: libx265 - Scenario: Video On Demand
FFmpeg
Encoder: libx265 - Scenario: Video On Demand
FFmpeg
Encoder: libx265 - Scenario: Platform
FFmpeg
Encoder: libx265 - Scenario: Platform
FFmpeg
Encoder: libx265 - Scenario: Upload
FFmpeg
Encoder: libx265 - Scenario: Upload
Mobile Neural Network
Model: inception-v3
Mobile Neural Network
Model: mobilenet-v1-1.0
Mobile Neural Network
Model: MobileNetV2_224
Mobile Neural Network
Model: SqueezeNetV1.0
Mobile Neural Network
Model: resnet-v2-50
Mobile Neural Network
Model: squeezenetv1.1
Mobile Neural Network
Model: mobilenetV3
Mobile Neural Network
Model: nasnet
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Execution Time
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Mesh Time
TensorFlow
Device: CPU - Batch Size: 64 - Model: GoogLeNet
FFmpeg
Encoder: libx264 - Scenario: Video On Demand
FFmpeg
Encoder: libx264 - Scenario: Video On Demand
FFmpeg
Encoder: libx264 - Scenario: Platform
FFmpeg
Encoder: libx264 - Scenario: Platform
WebP2 Image Encode
Encode Settings: Quality 75, Compression Effort 7
OpenRadioss
Model: Rubber O-Ring Seal Installation
Scikit-Learn
Benchmark: Sparse Random Projections, 100 Iterations
TensorFlow
Device: CPU - Batch Size: 16 - Model: ResNet-50
OpenRadioss
Model: Bumper Beam
libavif avifenc
Encoder Speed: 0
Blender
Blend File: BMW27 - Compute: CPU-Only
JPEG XL libjxl
Input: JPEG - Quality: 80
Xmrig
Variant: Monero - Hash Count: 1M
JPEG XL libjxl
Input: PNG - Quality: 80
AOM AV1
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K
Xmrig
Variant: Wownero - Hash Count: 1M
OpenRadioss
Model: Cell Phone Drop Test
Timed Erlang/OTP Compilation
Time To Compile
Scikit-Learn
Benchmark: MNIST Dataset
JPEG XL libjxl
Input: JPEG - Quality: 90
JPEG XL libjxl
Input: PNG - Quality: 90
TensorFlow
Device: CPU - Batch Size: 32 - Model: GoogLeNet
spaCy
Model: en_core_web_trf
spaCy
Model: en_core_web_lg
AOM AV1
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K
TensorFlow
Device: CPU - Batch Size: 64 - Model: AlexNet
FFmpeg
Encoder: libx265 - Scenario: Live
FFmpeg
Encoder: libx265 - Scenario: Live
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
nginx
Connections: 500
nginx
Connections: 1000
nginx
Connections: 100
nginx
Connections: 200
nginx
Connections: 20
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
libavif avifenc
Encoder Speed: 2
AOM AV1
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
miniBUDE
Implementation: OpenMP - Input Deck: BM1
miniBUDE
Implementation: OpenMP - Input Deck: BM1
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
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
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
Timed PHP Compilation
Time To Compile
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
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
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
JPEG XL Decoding libjxl
CPU Threads: 1
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
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
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
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
GraphicsMagick
Operation: Sharpen
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
GraphicsMagick
Operation: Noise-Gaussian
GraphicsMagick
Operation: Enhanced
Facebook RocksDB
Test: Read Random Write Random
Facebook RocksDB
Test: Update Random
Facebook RocksDB
Test: Read While Writing
GraphicsMagick
Operation: Swirl
Facebook RocksDB
Test: Random Read
GraphicsMagick
Operation: Resizing
GraphicsMagick
Operation: Rotate
GraphicsMagick
Operation: HWB Color Space
AOM AV1
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p
TensorFlow
Device: CPU - Batch Size: 16 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 32 - Model: AlexNet
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
FFmpeg
Encoder: libx264 - Scenario: Live
FFmpeg
Encoder: libx264 - Scenario: Live
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 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 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
Natron
Input: Spaceship
Y-Cruncher
Pi Digits To Calculate: 1B
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
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
WebP Image Encode
Encode Settings: Quality 100, Lossless, Highest Compression
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
srsRAN
Test: OFDM_Test
EnCodec
Target Bandwidth: 24 kbps
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: 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 Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream
Scikit-Learn
Benchmark: TSNE MNIST Dataset
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
AOM AV1
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p
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
EnCodec
Target Bandwidth: 3 kbps
TensorFlow
Device: CPU - Batch Size: 16 - Model: AlexNet
EnCodec
Target Bandwidth: 6 kbps
EnCodec
Target Bandwidth: 1.5 kbps
Cpuminer-Opt
Algorithm: Magi
Cpuminer-Opt
Algorithm: x25x
Cpuminer-Opt
Algorithm: Ringcoin
Stress-NG
Test: Glibc Qsort Data Sorting
Stress-NG
Test: Context Switching
Stress-NG
Test: Malloc
Stress-NG
Test: NUMA
Stress-NG
Test: System V Message Passing
Stress-NG
Test: IO_uring
Stress-NG
Test: Atomic
Stress-NG
Test: MMAP
Stress-NG
Test: Memory Copying
Stress-NG
Test: Futex
Stress-NG
Test: Matrix Math
Stress-NG
Test: CPU Cache
Stress-NG
Test: Forking
Stress-NG
Test: MEMFD
Stress-NG
Test: Glibc C String Functions
Stress-NG
Test: Socket Activity
Stress-NG
Test: Vector Math
Stress-NG
Test: Semaphores
Stress-NG
Test: CPU Stress
Stress-NG
Test: SENDFILE
Stress-NG
Test: Crypto
Stress-NG
Test: Mutex
Cpuminer-Opt
Algorithm: Myriad-Groestl
Cpuminer-Opt
Algorithm: Garlicoin
Cpuminer-Opt
Algorithm: Triple SHA-256, Onecoin
Cpuminer-Opt
Algorithm: LBC, LBRY Credits
Cpuminer-Opt
Algorithm: Deepcoin
Cpuminer-Opt
Algorithm: Quad SHA-256, Pyrite
Cpuminer-Opt
Algorithm: Blake-2 S
Cpuminer-Opt
Algorithm: Skeincoin
AOM AV1
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K
Cpuminer-Opt
Algorithm: scrypt
7-Zip Compression
Test: Decompression Rating
7-Zip Compression
Test: Compression Rating
JPEG XL Decoding libjxl
CPU Threads: All
AOM AV1
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p
srsRAN
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
srsRAN
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
Y-Cruncher
Pi Digits To Calculate: 500M
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
FLAC Audio Encoding
WAV To FLAC
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
AOM AV1
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K
Timed CPython Compilation
Build Configuration: Default
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
WebP Image Encode
Encode Settings: Quality 100, Lossless
C-Blosc
Test: blosclz bitshuffle
AOM AV1
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
SMHasher
Hash: FarmHash128
SMHasher
Hash: FarmHash128
AOM AV1
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p
SMHasher
Hash: MeowHash x86_64 AES-NI
SMHasher
Hash: MeowHash x86_64 AES-NI
libavif avifenc
Encoder Speed: 6, Lossless
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
SMHasher
Hash: Spooky32
SMHasher
Hash: Spooky32
SMHasher
Hash: FarmHash32 x86_64 AVX
SMHasher
Hash: FarmHash32 x86_64 AVX
SMHasher
Hash: fasthash32
SMHasher
Hash: fasthash32
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
SMHasher
Hash: t1ha2_atonce
SMHasher
Hash: t1ha2_atonce
SMHasher
Hash: t1ha0_aes_avx2 x86_64
SMHasher
Hash: t1ha0_aes_avx2 x86_64
AOM AV1
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p
libavif avifenc
Encoder Speed: 6
Unpacking The Linux Kernel
linux-5.19.tar.xz
WebP Image Encode
Encode Settings: Quality 100, Highest Compression
WebP2 Image Encode
Encode Settings: Quality 100, Compression Effort 5
SMHasher
Hash: wyhash
SMHasher
Hash: wyhash
AOM AV1
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p
libavif avifenc
Encoder Speed: 10, Lossless
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
AOM AV1
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p
C-Blosc
Test: blosclz shuffle
WebP2 Image Encode
Encode Settings: Default
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
WebP Image Encode
Encode Settings: Quality 100
WebP Image Encode
Encode Settings: Default
Phoronix Test Suite v10.8.5