Ubuntu 23.10 Server Benchmarks

2 x Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2310301-NE-UBUNTU23169&grw.

TSCP

AI Chess Performance

Stress-NG

Test: NUMA

Stress-NG

Test: CPU Stress

Stress-NG

Test: Matrix Math

Stress-NG

Test: AVX-512 VNNI

SPECFEM3D

Model: Layered Halfspace

Stress-NG

Test: Vector Math

Stress-NG

Test: Floating Point

Stress-NG

Test: Matrix 3D Math

Helsing

Digit Range: 14 digit

Stress-NG

Test: Memory Copying

Stress-NG

Test: Vector Shuffle

Stress-NG

Test: Wide Vector Math

SPECFEM3D

Model: Mount St. Helens

Stress-NG

Test: Fused Multiply-Add

ASTC Encoder

Preset: Medium

SPECFEM3D

Model: Tomographic Model

Stress-NG

Test: IO_uring

SPECFEM3D

Model: Homogeneous Halfspace

Crafty

Elapsed Time

SPECFEM3D

Model: Water-layered Halfspace

Stress-NG

Test: Vector Floating Point

ASTC Encoder

Preset: Thorough

RawTherapee

Total Benchmark Time

libxsmm

M N K: 128

ASTC Encoder

Preset: Exhaustive

libxsmm

M N K: 256

KTX-Software toktx

Settings: Zstd Compression 9

libxsmm

M N K: 64

HeFFTe - Highly Efficient FFT for Exascale

Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128

HeFFTe - Highly Efficient FFT for Exascale

Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256

KTX-Software toktx

Settings: Zstd Compression 19

WebP Image Encode

Encode Settings: Default

WebP Image Encode

Encode Settings: Quality 100

WebP Image Encode

Encode Settings: Quality 100, Lossless

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240

WebP Image Encode

Encode Settings: Quality 100, Highest Compression

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200

WebP Image Encode

Encode Settings: Quality 100, Lossless, Highest Compression

SecureMark

Benchmark: SecureMark-TLS

Xmrig

Variant: Monero - Hash Count: 1M

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400

Xmrig

Variant: Wownero - Hash Count: 1M

Graph500

Scale: 26

Graph500

Scale: 26

Graph500

Scale: 26

Graph500

Scale: 26

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: Chrysler Neon 1M

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

Timed MAFFT Alignment

Multiple Sequence Alignment - LSU RNA

TensorFlow

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

TensorFlow

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

TensorFlow

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

TensorFlow

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

CloverLeaf

Input: clover_bm

CloverLeaf

Input: clover_bm16

CloverLeaf

Input: clover_bm64_short

GROMACS

Implementation: MPI CPU - Input: water_GMX50_bare

High Performance Conjugate Gradient

X Y Z: 104 104 104 - RT: 60

High Performance Conjugate Gradient

X Y Z: 144 144 144 - RT: 60

NAS Parallel Benchmarks

Test / Class: BT.C

NAS Parallel Benchmarks

Test / Class: CG.C

NAS Parallel Benchmarks

Test / Class: EP.D

NAS Parallel Benchmarks

Test / Class: FT.C

NAS Parallel Benchmarks

Test / Class: IS.D

NAS Parallel Benchmarks

Test / Class: LU.C

NAS Parallel Benchmarks

Test / Class: MG.C

NAS Parallel Benchmarks

Test / Class: SP.C

Rodinia

Test: OpenMP LavaMD

Rodinia

Test: OpenMP HotSpot3D

Rodinia

Test: OpenMP Leukocyte

Rodinia

Test: OpenMP CFD Solver

Rodinia

Test: OpenMP Streamcluster

NAMD

ATPase Simulation - 327,506 Atoms

oneDNN

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

oneDNN

Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU

oneDNN

Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU

oneDNN

Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU

oneDNN

Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU

oneDNN

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

oneDNN

Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - 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: Face Detection Retail FP16 - Device: CPU

OpenVINO

Model: Face Detection Retail FP16 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16 - 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: Face Detection Retail FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection Retail FP16-INT8 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16-INT8 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16-INT8 - 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: Handwritten English Recognition FP16 - Device: CPU

OpenVINO

Model: Handwritten English Recognition 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: Handwritten English Recognition FP16-INT8 - Device: CPU

OpenVINO

Model: Handwritten English Recognition FP16-INT8 - Device: CPU

OpenVINO

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

OpenVINO

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

ASKAP

Test: tConvolve MT - Gridding

ASKAP

Test: tConvolve MT - Degridding

ASKAP

Test: tConvolve MPI - Degridding

ASKAP

Test: tConvolve MPI - Gridding

ASKAP

Test: tConvolve OpenMP - Gridding

ASKAP

Test: tConvolve OpenMP - Degridding

ASKAP

Test: Hogbom Clean OpenMP

ACES DGEMM

Sustained Floating-Point Rate

Pennant

Test: sedovbig

Pennant

Test: leblancbig

Algebraic Multi-Grid Benchmark

LULESH

NWChem

Input: C240 Buckyball

QMCPACK

Input: H4_ae

QMCPACK

Input: Li2_STO_ae

QMCPACK

Input: LiH_ae_MSD

QMCPACK

Input: simple-H2O

QMCPACK

Input: O_ae_pyscf_UHF

QMCPACK

Input: FeCO6_b3lyp_gms

miniFE

Problem Size: Small

Xcompact3d Incompact3d

Input: X3D-benchmarking input.i3d

Xcompact3d Incompact3d

Input: input.i3d 129 Cells Per Direction

Xcompact3d Incompact3d

Input: input.i3d 193 Cells Per Direction

Coremark

CoreMark Size 666 - Iterations Per Second

Aircrack-ng

Primesieve

Length: 1e12

Primesieve

Length: 1e13

Timed Apache Compilation

Time To Compile

Stockfish

Total Time

7-Zip Compression

Test: Compression Rating

7-Zip Compression

Test: Decompression Rating

John The Ripper

Test: bcrypt

John The Ripper

Test: WPA PSK

John The Ripper

Test: Blowfish

John The Ripper

Test: HMAC-SHA512

John The Ripper

Test: MD5

Timed LLVM Compilation

Build System: Ninja

asmFish

1024 Hash Memory, 26 Depth

Cpuminer-Opt

Algorithm: Magi

Cpuminer-Opt

Algorithm: scrypt

Cpuminer-Opt

Algorithm: Deepcoin