df2888
Intel Xeon E E-2488 testing with a Supermicro Super Server X13SCL-F v0123456789 (1.1 BIOS) and llvmpipe on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403242-NE-DF288805368&gru&rdt.
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection Retail 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: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16 - Device: CPU
OpenVINO
Model: Person Re-Identification Retail FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
SVT-HEVC
Tuning: 1 - Input: Bosphorus 4K
SVT-HEVC
Tuning: 7 - Input: Bosphorus 4K
SVT-HEVC
Tuning: 10 - Input: Bosphorus 4K
SVT-HEVC
Tuning: 1 - Input: Bosphorus 1080p
SVT-HEVC
Tuning: 7 - Input: Bosphorus 1080p
SVT-HEVC
Tuning: 10 - Input: Bosphorus 1080p
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 4K
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 1080p
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 4K
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 4K
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
uvg266
Video Input: Bosphorus 4K - Video Preset: Slow
uvg266
Video Input: Bosphorus 4K - Video Preset: Medium
uvg266
Video Input: Bosphorus 1080p - Video Preset: Slow
uvg266
Video Input: Bosphorus 1080p - Video Preset: Medium
uvg266
Video Input: Bosphorus 4K - Video Preset: Very Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Super Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Very Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Super Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
VVenC
Video Input: Bosphorus 4K - Video Preset: Fast
VVenC
Video Input: Bosphorus 4K - Video Preset: Faster
VVenC
Video Input: Bosphorus 1080p - Video Preset: Fast
VVenC
Video Input: Bosphorus 1080p - Video Preset: Faster
x264
Video Input: Bosphorus 4K
x264
Video Input: Bosphorus 1080p
x265
Video Input: Bosphorus 4K
x265
Video Input: Bosphorus 1080p
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
7-Zip Compression
Test: Compression Rating
7-Zip Compression
Test: Decompression Rating
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
NAMD
Input: ATPase with 327,506 Atoms
NAMD
Input: STMV with 1,066,628 Atoms
ClickHouse
100M Rows Hits Dataset, First Run / Cold Cache
ClickHouse
100M Rows Hits Dataset, Second Run
ClickHouse
100M Rows Hits Dataset, Third Run
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Write
PostgreSQL
Scaling Factor: 1000 - Clients: 800 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Write
PostgreSQL
Scaling Factor: 1000 - Clients: 1000 - Mode: Read Only
PostgreSQL
Scaling Factor: 1000 - Clients: 800 - Mode: Read Write
PostgreSQL
Scaling Factor: 1000 - Clients: 1000 - Mode: Read Write
BRL-CAD
VGR Performance Metric
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1000 - Clients: 800 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1000 - Clients: 1000 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1000 - Clients: 800 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1000 - Clients: 1000 - Mode: Read Write - Average Latency
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection Retail 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: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16 - Device: CPU
OpenVINO
Model: Person Re-Identification Retail FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Mesh Time
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Execution Time
OpenFOAM
Input: drivaerFastback, Medium Mesh Size - Mesh Time
OpenFOAM
Input: drivaerFastback, Medium Mesh Size - Execution Time
SPECFEM3D
Model: Mount St. Helens
SPECFEM3D
Model: Layered Halfspace
SPECFEM3D
Model: Tomographic Model
SPECFEM3D
Model: Homogeneous Halfspace
SPECFEM3D
Model: Water-layered Halfspace
Timed FFmpeg Compilation
Time To Compile
Timed GCC Compilation
Time To Compile
Timed Godot Game Engine Compilation
Time To Compile
Timed Linux Kernel Compilation
Build: defconfig
Timed Linux Kernel Compilation
Build: allmodconfig
Timed LLVM Compilation
Build System: Ninja
Timed LLVM Compilation
Build System: Unix Makefiles
Timed Node.js Compilation
Time To Compile
Blender
Blend File: BMW27 - Compute: CPU-Only
Blender
Blend File: Classroom - Compute: CPU-Only
Blender
Blend File: Fishy Cat - Compute: CPU-Only
Blender
Blend File: Barbershop - Compute: CPU-Only
Blender
Blend File: Pabellon Barcelona - Compute: CPU-Only
Phoronix Test Suite v10.8.5