AMD EPYC 7543 Tyan Linux Benchmarks
AMD EPYC 7543 Linux distribution benchmarks by Michael Larabel
HTML result view exported from: https://openbenchmarking.org/result/2106272-IB-AMDTYAN3431&sor.
High Performance Conjugate Gradient
NAS Parallel Benchmarks
Test / Class: IS.D
miniFE
Problem Size: Small
NAMD
ATPase Simulation - 327,506 Atoms
Xcompact3d Incompact3d
Input: input.i3d 193 Cells Per Direction
LuxCoreRender
Scene: Danish Mood - Acceleration: CPU
LuxCoreRender
Scene: Rainbow Colors and Prism - Acceleration: CPU
OSPray
Demo: NASA Streamlines - Renderer: Path Tracer
Embree
Binary: Pathtracer ISPC - Model: Crown
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-HEVC
Tuning: 7 - Input: Bosphorus 1080p
SVT-HEVC
Tuning: 10 - Input: Bosphorus 1080p
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 1080p
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
VP9 libvpx Encoding
Speed: Speed 0 - Input: Bosphorus 4K
VP9 libvpx Encoding
Speed: Speed 5 - Input: Bosphorus 4K
Intel Open Image Denoise
Run: RT.hdr_alb_nrm.3840x2160
Intel Open Image Denoise
Run: RT.ldr_alb_nrm.3840x2160
Intel Open Image Denoise
Run: RTLightmap.hdr.4096x4096
OpenVKL
Benchmark: vklBenchmark
libavif avifenc
Encoder Speed: 10
libavif avifenc
Encoder Speed: 6, Lossless
libavif avifenc
Encoder Speed: 10, Lossless
Timed Linux Kernel Compilation
Time To Compile
Timed LLVM Compilation
Build System: Ninja
Timed LLVM Compilation
Build System: Unix Makefiles
Timed Node.js Compilation
Time To Compile
Timed Wasmer Compilation
Time To Compile
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
TensorFlow Lite
Model: SqueezeNet
TensorFlow Lite
Model: Inception V4
TensorFlow Lite
Model: Mobilenet Float
TensorFlow Lite
Model: Mobilenet Quant
TensorFlow Lite
Model: Inception ResNet V2
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: inception-v3
TNN
Target: CPU - Model: DenseNet
TNN
Target: CPU - Model: MobileNet v2
TNN
Target: CPU - Model: SqueezeNet v2
PlaidML
FP16: No - Mode: Inference - Network: VGG16 - Device: CPU
PlaidML
FP16: No - Mode: Inference - Network: VGG19 - Device: CPU
PlaidML
FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU
Blender
Blend File: Classroom - Compute: CPU-Only
Blender
Blend File: Barbershop - Compute: CPU-Only
ONNX Runtime
Model: yolov4 - Device: OpenMP CPU
ONNX Runtime
Model: bertsquad-10 - Device: OpenMP CPU
ONNX Runtime
Model: shufflenet-v2-10 - Device: OpenMP CPU
ONNX Runtime
Model: super-resolution-10 - Device: OpenMP CPU
Kripke
Phoronix Test Suite v10.8.5