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&export=txt&rdt&grw.

SMHasher

Hash: wyhash

SMHasher

Hash: SHA3-256

SMHasher

Hash: Spooky32

SMHasher

Hash: fasthash32

SMHasher

Hash: FarmHash128

SMHasher

Hash: t1ha2_atonce

SMHasher

Hash: FarmHash32 x86_64 AVX

SMHasher

Hash: t1ha0_aes_avx2 x86_64

SMHasher

Hash: MeowHash x86_64 AES-NI

Stress-NG

Test: MMAP

Stress-NG

Test: NUMA

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: IO_uring

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: 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

FLAC Audio Encoding

WAV To FLAC

BRL-CAD

VGR Performance Metric

JPEG XL Decoding libjxl

CPU Threads: 1

JPEG XL Decoding libjxl

CPU Threads: All

JPEG XL libjxl

Input: PNG - Quality: 80

JPEG XL libjxl

Input: PNG - Quality: 90

JPEG XL libjxl

Input: JPEG - Quality: 80

JPEG XL libjxl

Input: JPEG - Quality: 90

JPEG XL libjxl

Input: PNG - Quality: 100

JPEG XL libjxl

Input: JPEG - Quality: 100

WebP2 Image Encode

Encode Settings: Default

WebP2 Image Encode

Encode Settings: Quality 75, Compression Effort 7

WebP2 Image Encode

Encode Settings: Quality 95, Compression Effort 7

WebP2 Image Encode

Encode Settings: Quality 100, Compression Effort 5

WebP2 Image Encode

Encode Settings: Quality 100, Lossless Compression

WebP Image Encode

Encode Settings: Default

WebP Image Encode

Encode Settings: Quality 100

WebP Image Encode

Encode Settings: Quality 100, Lossless

WebP Image Encode

Encode Settings: Quality 100, Highest Compression

WebP Image Encode

Encode Settings: Quality 100, Lossless, Highest Compression

Xmrig

Variant: Monero - Hash Count: 1M

Xmrig

Variant: Wownero - Hash Count: 1M

miniBUDE

Implementation: OpenMP - Input Deck: BM1

miniBUDE

Implementation: OpenMP - Input Deck: BM1

miniBUDE

Implementation: OpenMP - Input Deck: BM2

miniBUDE

Implementation: OpenMP - Input Deck: BM2

OpenRadioss

Model: Bumper Beam

OpenRadioss

Model: Cell Phone Drop Test

OpenRadioss

Model: Bird Strike on Windshield

OpenRadioss

Model: Rubber O-Ring Seal Installation

OpenRadioss

Model: INIVOL and Fluid Structure Interaction Drop Container

TensorFlow

Device: CPU - Batch Size: 16 - Model: AlexNet

TensorFlow

Device: CPU - Batch Size: 32 - Model: AlexNet

TensorFlow

Device: CPU - Batch Size: 64 - Model: AlexNet

TensorFlow

Device: CPU - Batch Size: 256 - Model: AlexNet

TensorFlow

Device: CPU - Batch Size: 512 - Model: AlexNet

TensorFlow

Device: CPU - Batch Size: 16 - Model: GoogLeNet

TensorFlow

Device: CPU - Batch Size: 16 - Model: ResNet-50

Y-Cruncher

Pi Digits To Calculate: 500M

TensorFlow

Device: CPU - Batch Size: 32 - Model: GoogLeNet

TensorFlow

Device: CPU - Batch Size: 32 - Model: ResNet-50

TensorFlow

Device: CPU - Batch Size: 64 - Model: GoogLeNet

TensorFlow

Device: CPU - Batch Size: 64 - Model: ResNet-50

TensorFlow

Device: CPU - Batch Size: 256 - Model: ResNet-50

Scikit-Learn

Benchmark: MNIST Dataset

Scikit-Learn

Benchmark: TSNE MNIST Dataset

Scikit-Learn

Benchmark: Sparse Random Projections, 100 Iterations

Mobile Neural Network

Model: nasnet

Mobile Neural Network

Model: mobilenetV3

Mobile Neural Network

Model: squeezenetv1.1

Mobile Neural Network

Model: resnet-v2-50

Mobile Neural Network

Model: SqueezeNetV1.0

Mobile Neural Network

Model: MobileNetV2_224

Mobile Neural Network

Model: mobilenet-v1-1.0

Y-Cruncher

Pi Digits To Calculate: 1B

TensorFlow

Device: CPU - Batch Size: 256 - Model: GoogLeNet

Mobile Neural Network

Model: inception-v3

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 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: 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

spaCy

Model: en_core_web_lg

spaCy

Model: en_core_web_trf

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: 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: 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

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

OpenFOAM

Input: drivaerFastback, Small Mesh Size - Mesh Time

OpenFOAM

Input: drivaerFastback, Small Mesh Size - Execution Time

7-Zip Compression

Test: Compression Rating