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Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and llvmpipe on Ubuntu 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2311069-PTS-AUG6407629&rdt&grs.

OpenVINO

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

OpenVINO

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

C-Blosc

Test: blosclz shuffle - Buffer Size: 8MB

oneDNN

Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU

QMCPACK

Input: H4_ae

oneDNN

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

HeFFTe - Highly Efficient FFT for Exascale

Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256

HeFFTe - Highly Efficient FFT for Exascale

Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128

oneDNN

Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU

oneDNN

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

oneDNN

Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU

oneDNN

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

HeFFTe - Highly Efficient FFT for Exascale

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

Intel Open Image Denoise

Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only

oneDNN

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

HeFFTe - Highly Efficient FFT for Exascale

Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256

oneDNN

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

oneDNN

Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU

OpenVINO

Model: Handwritten English Recognition FP16 - Device: CPU

OpenVINO

Model: Handwritten English Recognition FP16 - Device: CPU

HeFFTe - Highly Efficient FFT for Exascale

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

QMCPACK

Input: O_ae_pyscf_UHF

C-Blosc

Test: blosclz bitshuffle - Buffer Size: 16MB

QMCPACK

Input: Li2_STO_ae

OpenVINO

Model: Vehicle Detection FP16 - Device: CPU

OpenVINO

Model: Vehicle Detection FP16 - Device: CPU

OpenVINO

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

C-Blosc

Test: blosclz noshuffle - Buffer Size: 16MB

Cpuminer-Opt

Algorithm: Skeincoin

HeFFTe - Highly Efficient FFT for Exascale

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

OpenVINO

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

HeFFTe - Highly Efficient FFT for Exascale

Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512

oneDNN

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

OpenVINO

Model: Person Detection FP16 - Device: CPU

C-Blosc

Test: blosclz bitshuffle - Buffer Size: 128MB

OpenVINO

Model: Person Detection FP16 - Device: CPU

OpenVINO

Model: Person Detection FP32 - Device: CPU

OpenVINO

Model: Person Detection FP32 - Device: CPU

HeFFTe - Highly Efficient FFT for Exascale

Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512

C-Blosc

Test: blosclz shuffle - Buffer Size: 32MB

oneDNN

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

HeFFTe - Highly Efficient FFT for Exascale

Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512

OpenVINO

Model: Face Detection Retail FP16 - Device: CPU

C-Blosc

Test: blosclz bitshuffle - Buffer Size: 32MB

OpenVINO

Model: Face Detection Retail FP16 - Device: CPU

HeFFTe - Highly Efficient FFT for Exascale

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

OpenVINO

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

C-Blosc

Test: blosclz shuffle - Buffer Size: 256MB

OpenVINO

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

OpenVINO

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

Embree

Binary: Pathtracer - Model: Asian Dragon

oneDNN

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

C-Blosc

Test: blosclz bitshuffle - Buffer Size: 64MB

oneDNN

Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU

QuantLib

Configuration: Multi-Threaded

OpenVINO

Model: Face Detection FP16 - Device: CPU

Embree

Binary: Pathtracer - Model: Crown

OSPRay Studio

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

OSPRay Studio

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

CloverLeaf

Input: clover_bm64_short

OpenVINO

Model: Face Detection FP16 - Device: CPU

C-Blosc

Test: blosclz shuffle - Buffer Size: 16MB

Cpuminer-Opt

Algorithm: Garlicoin

C-Blosc

Test: blosclz noshuffle - Buffer Size: 128MB

C-Blosc

Test: blosclz bitshuffle - Buffer Size: 256MB

Cpuminer-Opt

Algorithm: scrypt

OSPRay Studio

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

OpenVINO

Model: Weld Porosity Detection FP16 - Device: CPU

oneDNN

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

Embree

Binary: Pathtracer ISPC - Model: Crown

OpenVINO

Model: Weld Porosity Detection FP16 - Device: CPU

OSPRay Studio

Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU

OSPRay Studio

Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU

OSPRay Studio

Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU

C-Blosc

Test: blosclz noshuffle - Buffer Size: 8MB

OpenVINO

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

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

oneDNN

Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU

HeFFTe - Highly Efficient FFT for Exascale

Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

Cpuminer-Opt

Algorithm: Myriad-Groestl

OSPRay Studio

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

HeFFTe - Highly Efficient FFT for Exascale

Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128

C-Blosc

Test: blosclz noshuffle - Buffer Size: 64MB

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

C-Blosc

Test: blosclz noshuffle - Buffer Size: 32MB

oneDNN

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

QMCPACK

Input: LiH_ae_MSD

oneDNN

Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU

Cpuminer-Opt

Algorithm: Triple SHA-256, Onecoin

C-Blosc

Test: blosclz noshuffle - Buffer Size: 256MB

OSPRay Studio

Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU

C-Blosc

Test: blosclz shuffle - Buffer Size: 128MB

OSPRay Studio

Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU

OSPRay Studio

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

OpenVINO

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

OpenVINO

Model: Road Segmentation ADAS FP16 - Device: CPU

OpenVINO

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

OpenVINO

Model: Road Segmentation ADAS FP16 - Device: CPU

OSPRay Studio

Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU

QMCPACK

Input: FeCO6_b3lyp_gms

Embree

Binary: Pathtracer - Model: Asian Dragon Obj

oneDNN

Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU

oneDNN

Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU

C-Blosc

Test: blosclz bitshuffle - Buffer Size: 8MB

oneDNN

Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU

OSPRay Studio

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

Embree

Binary: Pathtracer ISPC - Model: Asian Dragon Obj

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200

oneDNN

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

OpenVINO

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

QuantLib

Configuration: Single-Threaded

OSPRay Studio

Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU

OSPRay Studio

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

QMCPACK

Input: simple-H2O

Timed Gem5 Compilation

Time To Compile

Cpuminer-Opt

Algorithm: Deepcoin

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240

C-Blosc

Test: blosclz shuffle - Buffer Size: 64MB

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

Cpuminer-Opt

Algorithm: Ringcoin

Cpuminer-Opt

Algorithm: Magi

Cpuminer-Opt

Algorithm: LBC, LBRY Credits

Embree

Binary: Pathtracer ISPC - Model: Asian Dragon

OSPRay Studio

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

OSPRay Studio

Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU

CloverLeaf

Input: clover_bm

OSPRay Studio

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

OpenVINO

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

OpenVINO

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

OpenVINO

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

Cpuminer-Opt

Algorithm: Quad SHA-256, Pyrite

Cpuminer-Opt

Algorithm: Blake-2 S

OSPRay Studio

Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU

OpenVKL

Benchmark: vklBenchmarkCPU Scalar

OpenVKL

Benchmark: vklBenchmarkCPU ISPC

Intel Open Image Denoise

Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only

Intel Open Image Denoise

Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only

Phoronix Test Suite v10.8.4