AMD AOCC 4.0 Benchmarks

AMD Ryzen 9 7950X compiler benchmarks by Michael Larabel for a future article.

HTML result view exported from: https://openbenchmarking.org/result/2211152-PTS-AMDAOCC460&grr&sor.

JPEG XL libjxl

Input: JPEG - Quality: 100

ONNX Runtime

Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard

LeelaChessZero

Backend: BLAS

LeelaChessZero

Backend: Eigen

Crypto++

Test: Keyed Algorithms

SecureMark

Benchmark: SecureMark-TLS

JPEG XL libjxl

Input: PNG - Quality: 100

TNN

Target: CPU - Model: DenseNet

ONNX Runtime

Model: GPT-2 - Device: CPU - Executor: Standard

ONNX Runtime

Model: yolov4 - Device: CPU - Executor: Standard

OpenSSL

Algorithm: SHA256

CppPerformanceBenchmarks

Test: Math Library

ONNX Runtime

Model: super-resolution-10 - Device: CPU - Executor: Parallel

ONNX Runtime

Model: GPT-2 - Device: CPU - Executor: Parallel

ONNX Runtime

Model: bertsquad-12 - Device: CPU - Executor: Parallel

ONNX Runtime

Model: yolov4 - Device: CPU - Executor: Parallel

ONNX Runtime

Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel

simdjson

Throughput Test: Kostya

ONNX Runtime

Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel

SVT-HEVC

Tuning: 1 - Input: Bosphorus 4K

NCNN

Target: CPU - Model: regnety_400m

NCNN

Target: CPU - Model: squeezenet_ssd

NCNN

Target: CPU - Model: yolov4-tiny

NCNN

Target: CPU - Model: resnet50

NCNN

Target: CPU - Model: alexnet

NCNN

Target: CPU - Model: resnet18

NCNN

Target: CPU - Model: vgg16

NCNN

Target: CPU - Model: googlenet

NCNN

Target: CPU - Model: blazeface

NCNN

Target: CPU - Model: efficientnet-b0

NCNN

Target: CPU - Model: mnasnet

NCNN

Target: CPU - Model: shufflenet-v2

NCNN

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

NCNN

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

NCNN

Target: CPU - Model: mobilenet

Caffe

Model: GoogleNet - Acceleration: CPU - Iterations: 100

simdjson

Throughput Test: LargeRandom

oneDNN

Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - 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: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU

JPEG XL libjxl

Input: JPEG - Quality: 90

JPEG XL libjxl

Input: PNG - Quality: 90

Monte Carlo Simulations of Ionised Nebulae

Input: Dust 2D tau100.0

libavif avifenc

Encoder Speed: 0

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

simdjson

Throughput Test: DistinctUserID

simdjson

Throughput Test: PartialTweets

simdjson

Throughput Test: TopTweet

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: Face Detection FP16 - Device: CPU

OpenVINO

Model: Face Detection FP16 - Device: CPU

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Machine Translation EN To DE FP16 - Device: CPU

OpenVINO

Model: Machine Translation EN To DE FP16 - Device: CPU

Ngspice

Circuit: C2670

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU

OpenVINO

Model: Age Gender Recognition Retail 0013 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 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

GraphicsMagick

Operation: Sharpen

GraphicsMagick

Operation: Noise-Gaussian

GraphicsMagick

Operation: Resizing

GraphicsMagick

Operation: Enhanced

GraphicsMagick

Operation: Rotate

OpenSSL

Algorithm: RSA4096

OpenSSL

Algorithm: RSA4096

GraphicsMagick

Operation: Swirl

GraphicsMagick

Operation: HWB Color Space

Ngspice

Circuit: C7552

Tachyon

Total Time

SVT-AV1

Encoder Mode: Preset 4 - Input: Bosphorus 4K

Redis

Test: SET - Parallel Connections: 50

Crypto++

Test: Unkeyed Algorithms

Kripke

PJSIP

Method: OPTIONS, Stateful

PJSIP

Method: INVITE

Zstd Compression

Compression Level: 19 - Decompression Speed

Zstd Compression

Compression Level: 19 - Compression Speed

Dragonflydb

Clients: 50 - Set To Get Ratio: 1:5

Dragonflydb

Clients: 50 - Set To Get Ratio: 5:1

AOM AV1

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

JPEG XL Decoding libjxl

CPU Threads: 1

QuantLib

CppPerformanceBenchmarks

Test: Stepanov Vector

Zstd Compression

Compression Level: 19, Long Mode - Decompression Speed

Zstd Compression

Compression Level: 19, Long Mode - Compression Speed

oneDNN

Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU

SQLite Speedtest

Timed Time - Size 1,000

Caffe

Model: AlexNet - Acceleration: CPU - Iterations: 100

Zstd Compression

Compression Level: 3 - Decompression Speed

Zstd Compression

Compression Level: 3 - Compression Speed

libavif avifenc

Encoder Speed: 2

CppPerformanceBenchmarks

Test: Ctype

Liquid-DSP

Threads: 8 - Buffer Length: 256 - Filter Length: 57

SVT-VP9

Tuning: VMAF Optimized - Input: Bosphorus 4K

WebP Image Encode

Encode Settings: Quality 100, Lossless, Highest Compression