Ubuntu 22.04 Server Benchmarks

AMD EPYC 7713 64-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2209132-NE-UBUNTU22004&grr&rdt.

WRF

Input: conus 2.5km

OpenFOAM

Input: drivaerFastback, Large Mesh Size - Execution Time

OpenFOAM

Input: drivaerFastback, Large Mesh Size - Mesh Time

SPECjbb 2015

SPECjbb2015-Composite critical-jOPS

SPECjbb 2015

SPECjbb2015-Composite max-jOPS

MariaDB

Clients: 4096

MariaDB

Clients: 2048

NWChem

Input: C240 Buckyball

Renaissance

Test: ALS Movie Lens

RELION

Test: Basic - Device: CPU

BRL-CAD

VGR Performance Metric

Xcompact3d Incompact3d

Input: X3D-benchmarking input.i3d

Rodinia

Test: OpenMP HotSpot3D

Stockfish

Total Time

LeelaChessZero

Backend: Eigen

LeelaChessZero

Backend: BLAS

Renaissance

Test: Savina Reactors.IO

Quantum ESPRESSO

Input: AUSURF112

oneDNN

Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 250 - Mode: Read Write

asmFish

1024 Hash Memory, 26 Depth

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 500 - Mode: Read Write

Renaissance

Test: Apache Spark PageRank

Graph500

Scale: 26

Graph500

Scale: 26

Graph500

Scale: 26

Graph500

Scale: 26

ONNX Runtime

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

ONNX Runtime

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

ONNX Runtime

Model: yolov4 - Device: CPU - Executor: Standard

ONNX Runtime

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

JPEG XL libjxl

Input: PNG - Encode Speed: 8

SecureMark

Benchmark: SecureMark-TLS

High Performance Conjugate Gradient

LuaRadio

Test: Complex Phase

LuaRadio

Test: Hilbert Transform

LuaRadio

Test: FM Deemphasis Filter

LuaRadio

Test: Five Back to Back FIR Filters

Blender

Blend File: Barbershop - Compute: CPU-Only

oneDNN

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

Mlpack Benchmark

Benchmark: scikit_qda

Timed Linux Kernel Compilation

Build: allmodconfig

TNN

Target: CPU - Model: DenseNet

OpenFOAM

Input: drivaerFastback, Small Mesh Size - Execution Time

OpenFOAM

Input: drivaerFastback, Small Mesh Size - Mesh Time

Timed LLVM Compilation

Build System: Unix Makefiles

Numpy Benchmark

LuxCoreRender

Scene: Danish Mood - Acceleration: CPU

LuxCoreRender

Scene: LuxCore Benchmark - Acceleration: CPU

LZ4 Compression

Compression Level: 3 - Decompression Speed

LZ4 Compression

Compression Level: 3 - Compression Speed

OpenSSL

Algorithm: SHA256

Timed Gem5 Compilation

Time To Compile

Appleseed

Scene: Material Tester

WebP2 Image Encode

Encode Settings: Quality 95, Compression Effort 7

OSPRay Studio

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

Timed Node.js Compilation

Time To Compile

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 500 - Mode: Read Only

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency

PostgreSQL pgbench

Scaling Factor: 100 - Clients: 250 - Mode: Read Only

OSPRay Studio

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

Ngspice

Circuit: C2670

Timed LLVM Compilation

Build System: Ninja

VP9 libvpx Encoding

Speed: Speed 5 - Input: Bosphorus 4K

LuxCoreRender

Scene: Orange Juice - Acceleration: CPU

Apache Cassandra

Test: Writes

ClickHouse

100M Rows Web Analytics Dataset, Third Run

ClickHouse

100M Rows Web Analytics Dataset, Second Run

ClickHouse

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

OSPRay Studio

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

OSPRay Studio

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

ONNX Runtime

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

ONNX Runtime

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

OSPRay Studio

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

OSPRay Studio

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

OSPRay Studio

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

OSPRay Studio

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

OSPRay Studio

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

Renaissance

Test: Genetic Algorithm Using Jenetics + Futures

NAS Parallel Benchmarks

Test / Class: EP.D

Renaissance

Test: In-Memory Database Shootout

Renaissance

Test: Finagle HTTP Requests

Ngspice

Circuit: C7552

etcd

Test: RANGE - Connections: 100 - Clients: 100 - Average Latency

etcd

Test: RANGE - Connections: 100 - Clients: 100

oneDNN

Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU

JPEG XL libjxl

Input: PNG - Encode Speed: 7

Appleseed

Scene: Emily

OpenVINO

Model: Face Detection FP16 - Device: CPU

OpenVINO

Model: Face Detection FP16 - Device: CPU

simdjson

Throughput Test: DistinctUserID

simdjson

Throughput Test: TopTweet

Apache HTTP Server

Concurrent Requests: 1000

Helsing

Digit Range: 14 digit

simdjson

Throughput Test: PartialTweets

Apache HTTP Server

Concurrent Requests: 500

nginx

Concurrent Requests: 500

nginx

Concurrent Requests: 1000

Sysbench

Test: CPU

Timed CPython Compilation

Build Configuration: Released Build, PGO + LTO Optimized

etcd

Test: PUT - Connections: 100 - Clients: 100 - Average Latency

etcd

Test: PUT - Connections: 100 - Clients: 100

oneDNN

Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU

oneDNN

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

etcd

Test: RANGE - Connections: 500 - Clients: 100 - Average Latency

etcd

Test: RANGE - Connections: 500 - Clients: 100

etcd

Test: PUT - Connections: 500 - Clients: 100 - Average Latency

etcd

Test: PUT - Connections: 500 - Clients: 100

etcd

Test: PUT - Connections: 100 - Clients: 1000 - Average Latency

etcd

Test: PUT - Connections: 100 - Clients: 1000

etcd

Test: RANGE - Connections: 100 - Clients: 1000 - Average Latency

etcd

Test: RANGE - Connections: 100 - Clients: 1000

ebizzy

Node.js V8 Web Tooling Benchmark

oneDNN

Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU

etcd

Test: PUT - Connections: 500 - Clients: 1000 - Average Latency

etcd

Test: PUT - Connections: 500 - Clients: 1000

etcd

Test: RANGE - Connections: 500 - Clients: 1000 - Average Latency

etcd

Test: RANGE - Connections: 500 - Clients: 1000

Blender

Blend File: Pabellon Barcelona - Compute: CPU-Only

OpenVINO

Model: Person Detection FP16 - Device: CPU

OpenVINO

Model: Person Detection FP16 - Device: CPU

LZ4 Compression

Compression Level: 9 - Decompression Speed

LZ4 Compression

Compression Level: 9 - Compression Speed

OpenVINO

Model: Person Detection FP32 - Device: CPU

OpenVINO

Model: Person Detection FP32 - Device: CPU

Dragonflydb

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

Dragonflydb

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

Dragonflydb

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

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

PyPerformance

Benchmark: python_startup

PJSIP

Method: INVITE

PJSIP

Method: OPTIONS, Stateful

OpenVINO

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

OpenVINO

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

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU