zen 1 epyc

2 x AMD EPYC 7601 32-Core testing with a Dell 02MJ3T (1.2.5 BIOS) and Matrox G200eW3 on Ubuntu 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2211196-NE-ZEN1EPYC153&sor&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

ASTC Encoder

Preset: Fast

ASTC Encoder

Preset: Medium

ASTC Encoder

Preset: Thorough

ASTC Encoder

Preset: Exhaustive

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

nekRS

Input: TurboPipe Periodic

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

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: GoogLeNet

TensorFlow

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

TensorFlow

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

TensorFlow

Device: CPU - Batch Size: 512 - Model: ResNet-50

AI Benchmark Alpha

Device Inference Score

AI Benchmark Alpha

Device Training Score

AI Benchmark Alpha

Device AI Score

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

Mobile Neural Network

Model: inception-v3

Y-Cruncher

Pi Digits To Calculate: 1B

Y-Cruncher

Pi Digits To Calculate: 500M

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

NCNN

Target: CPU - Model: mobilenet

NCNN

Target: CPU-v2-v2 - Model: mobilenet-v2

NCNN

Target: CPU-v3-v3 - Model: mobilenet-v3

NCNN

Target: CPU - Model: shufflenet-v2

NCNN

Target: CPU - Model: mnasnet

NCNN

Target: CPU - Model: efficientnet-b0

NCNN

Target: CPU - Model: blazeface

NCNN

Target: CPU - Model: googlenet

NCNN

Target: CPU - Model: vgg16

NCNN

Target: CPU - Model: resnet18

NCNN

Target: CPU - Model: alexnet

NCNN

Target: CPU - Model: resnet50

NCNN

Target: CPU - Model: yolov4-tiny

NCNN

Target: CPU - Model: squeezenet_ssd

NCNN

Target: CPU - Model: regnety_400m

NCNN

Target: CPU - Model: vision_transformer

NCNN

Target: CPU - Model: FastestDet

LAMMPS Molecular Dynamics Simulator

Model: 20k Atoms

LAMMPS Molecular Dynamics Simulator

Model: Rhodopsin Protein

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

OpenFOAM

Input: drivaerFastback, Medium Mesh Size - Mesh Time

OpenFOAM

Input: drivaerFastback, Medium Mesh Size - Execution Time

Aircrack-ng

Primesieve

Length: 1e12

Primesieve

Length: 1e13

Timed PHP Compilation

Time To Compile

Cpuminer-Opt

Algorithm: Magi

Cpuminer-Opt

Algorithm: x25x

Cpuminer-Opt

Algorithm: scrypt

Cpuminer-Opt

Algorithm: Deepcoin

Cpuminer-Opt

Algorithm: Ringcoin

Cpuminer-Opt

Algorithm: Blake-2 S

Cpuminer-Opt

Algorithm: Garlicoin

Cpuminer-Opt

Algorithm: Skeincoin

Cpuminer-Opt

Algorithm: Myriad-Groestl

Cpuminer-Opt

Algorithm: LBC, LBRY Credits

Cpuminer-Opt

Algorithm: Quad SHA-256, Pyrite

Cpuminer-Opt

Algorithm: Triple SHA-256, Onecoin

AOM AV1

Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K

AOM AV1

Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p

AOM AV1

Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p

AOM AV1

Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p

AOM AV1

Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p

AOM AV1

Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p

AOM AV1

Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p

AOM AV1

Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p

GraphicsMagick

Operation: Swirl

GraphicsMagick

Operation: Rotate

GraphicsMagick

Operation: Sharpen

GraphicsMagick

Operation: Enhanced

GraphicsMagick

Operation: Resizing

GraphicsMagick

Operation: Noise-Gaussian

GraphicsMagick

Operation: HWB Color Space

SVT-AV1

Encoder Mode: Preset 4 - Input: Bosphorus 4K

SVT-AV1

Encoder Mode: Preset 8 - Input: Bosphorus 4K

SVT-AV1

Encoder Mode: Preset 10 - Input: Bosphorus 4K

SVT-AV1

Encoder Mode: Preset 12 - Input: Bosphorus 4K

SVT-AV1

Encoder Mode: Preset 4 - Input: Bosphorus 1080p

SVT-AV1

Encoder Mode: Preset 8 - Input: Bosphorus 1080p

SVT-AV1

Encoder Mode: Preset 10 - Input: Bosphorus 1080p

SVT-AV1

Encoder Mode: Preset 12 - Input: Bosphorus 1080p

Blender

Blend File: BMW27 - Compute: CPU-Only

Blender

Blend File: Classroom - Compute: CPU-Only

Blender

Blend File: Fishy Cat - Compute: CPU-Only

Blender

Blend File: Barbershop - Compute: CPU-Only

Blender

Blend File: Pabellon Barcelona - Compute: CPU-Only

FFmpeg

Encoder: libx264 - Scenario: Live

FFmpeg

Encoder: libx264 - Scenario: Live

FFmpeg

Encoder: libx265 - Scenario: Live

FFmpeg

Encoder: libx265 - Scenario: Live

FFmpeg

Encoder: libx264 - Scenario: Upload

FFmpeg

Encoder: libx264 - Scenario: Upload

FFmpeg

Encoder: libx265 - Scenario: Upload

FFmpeg

Encoder: libx265 - Scenario: Upload

FFmpeg

Encoder: libx264 - Scenario: Platform

FFmpeg

Encoder: libx264 - Scenario: Platform

FFmpeg

Encoder: libx265 - Scenario: Platform

FFmpeg

Encoder: libx265 - Scenario: Platform

FFmpeg

Encoder: libx264 - Scenario: Video On Demand

FFmpeg

Encoder: libx264 - Scenario: Video On Demand

FFmpeg

Encoder: libx265 - Scenario: Video On Demand

FFmpeg

Encoder: libx265 - Scenario: Video On Demand

libavif avifenc

Encoder Speed: 0

libavif avifenc

Encoder Speed: 2

libavif avifenc

Encoder Speed: 6

EnCodec

Target Bandwidth: 24 kbps

libavif avifenc

Encoder Speed: 6, Lossless

libavif avifenc

Encoder Speed: 10, Lossless

Natron

Input: Spaceship

OSPRay Studio

Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer

OSPRay Studio

Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer

OSPRay Studio

Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer

OSPRay Studio

Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer

OSPRay Studio

Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer

OSPRay Studio

Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer

OSPRay Studio

Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer

OSPRay Studio

Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer

EnCodec

Target Bandwidth: 1.5 kbps

OSPRay Studio

Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer

OSPRay Studio

Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer

OSPRay Studio

Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer

OSPRay Studio

Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer

OSPRay Studio

Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer

OSPRay Studio

Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer

OSPRay Studio

Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer

OSPRay Studio

Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer

OSPRay Studio

Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer

OSPRay Studio

Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer

Timed CPython Compilation

Build Configuration: Default

Timed CPython Compilation

Build Configuration: Released Build, PGO + LTO Optimized

Timed Erlang/OTP Compilation

Time To Compile

Timed Node.js Compilation

Time To Compile

Timed Wasmer Compilation

Time To Compile

C-Blosc

Test: blosclz shuffle

C-Blosc

Test: blosclz bitshuffle

srsRAN

Test: OFDM_Test

srsRAN

Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM

srsRAN

Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM

srsRAN

Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM

EnCodec

Target Bandwidth: 6 kbps

srsRAN

Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM

srsRAN

Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM

srsRAN

Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM

srsRAN

Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM

srsRAN

Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM

srsRAN

Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM

srsRAN

Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM

nginx

Connections: 200

nginx

Connections: 500

nginx

Connections: 1000

EnCodec

Target Bandwidth: 3 kbps

ClickHouse

100M Rows Web Analytics Dataset, First Run / Cold Cache

ClickHouse

100M Rows Web Analytics Dataset, Second Run

Facebook RocksDB

Test: Random Read

Facebook RocksDB

Test: Update Random

Facebook RocksDB

Test: Read While Writing

Facebook RocksDB

Test: Read Random Write Random

Node.js V8 Web Tooling Benchmark

Unpacking The Linux Kernel

linux-5.19.tar.xz

ClickHouse

100M Rows Web Analytics Dataset, Third Run

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

Phoronix Test Suite v10.8.5