Oktoberfest Benchmarks
Intel Xeon Gold 5218R testing with a GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS) and llvmpipe on Ubuntu 18.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2010183-FI-OKTOBERFE24&grs&sro.
GROMACS
Water Benchmark
NAMD
ATPase Simulation - 327,506 Atoms
FFTE
N=256, 3D Complex FFT Routine
LAMMPS Molecular Dynamics Simulator
Model: 20k Atoms
LAMMPS Molecular Dynamics Simulator
Model: Rhodopsin Protein
TensorFlow Lite
Model: Inception ResNet V2
TensorFlow Lite
Model: Inception V4
TensorFlow Lite
Model: SqueezeNet
TensorFlow Lite
Model: Mobilenet Quant
TensorFlow Lite
Model: Mobilenet Float
Timed LLVM Compilation
Time To Compile
Incompact3D
Input: Cylinder
Zstd Compression
Compression Level: 19
Timed HMMer Search
Pfam Database Search
Zstd Compression
Compression Level: 3
Caffe
Model: GoogleNet - Acceleration: CPU - Iterations: 1000
Mobile Neural Network
Model: inception-v3
Caffe
Model: GoogleNet - Acceleration: CPU - Iterations: 200
Caffe
Model: AlexNet - Acceleration: CPU - Iterations: 1000
Caffe
Model: AlexNet - Acceleration: CPU - Iterations: 200
Caffe
Model: GoogleNet - Acceleration: CPU - Iterations: 100
Caffe
Model: AlexNet - Acceleration: CPU - Iterations: 100
InfluxDB
Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
InfluxDB
Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
InfluxDB
Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000
LibRaw
Post-Processing Benchmark
BYTE Unix Benchmark
Computational Test: Dhrystone 2
WebP Image Encode
Encode Settings: Quality 100, Lossless, Highest Compression
TNN
Target: CPU - Model: MobileNet v2
eSpeak-NG Speech Engine
Text-To-Speech Synthesis
WebP Image Encode
Encode Settings: Quality 100, Lossless
Hierarchical INTegration
Test: FLOAT
Dolfyn
Computational Fluid Dynamics
WebP Image Encode
Encode Settings: Quality 100
WebP Image Encode
Encode Settings: Quality 100, Highest Compression
WebP Image Encode
Encode Settings: Default
RNNoise
TNN
Target: CPU - Model: SqueezeNet v1.1
TensorFlow Lite
Model: NASNet Mobile
Kripke
Mobile Neural Network
Model: mobilenet-v1-1.0
Mobile Neural Network
Model: MobileNetV2_224
Mobile Neural Network
Model: resnet-v2-50
Mobile Neural Network
Model: SqueezeNetV1.0
Phoronix Test Suite v10.8.5