extra tests2
AMD EPYC 9334 32-Core testing with a Supermicro H13SSW (1.1 BIOS) and astdrmfb on AlmaLinux 9.2 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2310249-NE-EXTRATEST98&gru.
nekRS
Input: Kershaw
nekRS
Input: TurboPipe Periodic
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: Handwritten English Recognition 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
Embree
Binary: Pathtracer - Model: Crown
Embree
Binary: Pathtracer ISPC - Model: Crown
Embree
Binary: Pathtracer - Model: Asian Dragon
Embree
Binary: Pathtracer - Model: Asian Dragon Obj
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
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
Embree
Binary: Pathtracer - Model: Asian Dragon
Embree
Binary: Pathtracer - Model: Asian Dragon Obj
Embree
Binary: Pathtracer - Model: Crown
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
Embree
Binary: Pathtracer ISPC - Model: Crown
Intel Open Image Denoise
Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only
Intel Open Image Denoise
Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only
Intel Open Image Denoise
Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only
Intel Open Image Denoise
Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only
Intel Open Image Denoise
Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only
Intel Open Image Denoise
Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only
OpenVKL
Benchmark: vklBenchmarkCPU Scalar
OpenVKL
Benchmark: vklBenchmarkCPU ISPC
OSPRay
Benchmark: particle_volume/ao/real_time
OSPRay
Benchmark: particle_volume/scivis/real_time
OSPRay
Benchmark: particle_volume/pathtracer/real_time
OSPRay
Benchmark: gravity_spheres_volume/dim_512/ao/real_time
OSPRay
Benchmark: gravity_spheres_volume/dim_512/scivis/real_time
OSPRay
Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
QuantLib
Configuration: Single-Threaded
QuantLib
Configuration: Multi-Threaded
Apache Cassandra
Test: Writes
Apache Hadoop
Operation: Open - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Create - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Delete - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Create - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Create - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Delete - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Delete - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Rename - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Create - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Delete - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: File Status - Threads: 50 - Files: 100000
Apache Hadoop
Operation: File Status - Threads: 100 - Files: 100000
Apache Hadoop
Operation: File Status - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: File Status - Threads: 100 - Files: 1000000
TiDB Community Server
Test: oltp_read_write - Threads: 1
TiDB Community Server
Test: oltp_read_write - Threads: 16
TiDB Community Server
Test: oltp_read_write - Threads: 32
TiDB Community Server
Test: oltp_read_write - Threads: 64
TiDB Community Server
Test: oltp_point_select - Threads: 1
TiDB Community Server
Test: oltp_read_write - Threads: 128
TiDB Community Server
Test: oltp_update_index - Threads: 1
TiDB Community Server
Test: oltp_point_select - Threads: 16
TiDB Community Server
Test: oltp_point_select - Threads: 32
TiDB Community Server
Test: oltp_point_select - Threads: 64
TiDB Community Server
Test: oltp_update_index - Threads: 16
TiDB Community Server
Test: oltp_update_index - Threads: 32
TiDB Community Server
Test: oltp_update_index - Threads: 64
TiDB Community Server
Test: oltp_point_select - Threads: 128
TiDB Community Server
Test: oltp_update_index - Threads: 128
TiDB Community Server
Test: oltp_update_non_index - Threads: 1
TiDB Community Server
Test: oltp_update_non_index - Threads: 16
TiDB Community Server
Test: oltp_update_non_index - Threads: 32
TiDB Community Server
Test: oltp_update_non_index - Threads: 64
TiDB Community Server
Test: oltp_update_non_index - Threads: 128
Liquid-DSP
Threads: 1 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 1 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 2 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 2 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 4 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 4 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 8 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 8 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 1 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 16 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 16 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 2 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 32 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 32 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 4 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 64 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 64 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 8 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 96 - Buffer Length: 256 - Filter Length: 32
Liquid-DSP
Threads: 96 - Buffer Length: 256 - Filter Length: 57
Liquid-DSP
Threads: 16 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 32 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 64 - Buffer Length: 256 - Filter Length: 512
Liquid-DSP
Threads: 96 - Buffer Length: 256 - Filter Length: 512
Kripke
BRL-CAD
VGR Performance Metric
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: Handwritten English Recognition 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
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Remhos
Test: Sample Remap Example
SPECFEM3D
Model: Mount St. Helens
SPECFEM3D
Model: Layered Halfspace
SPECFEM3D
Model: Tomographic Model
SPECFEM3D
Model: Homogeneous Halfspace
SPECFEM3D
Model: Water-layered Halfspace
Timed Linux Kernel Compilation
Build: defconfig
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
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400
Phoronix Test Suite v10.8.5