extra tests
benchmarks for a future article.
HTML result view exported from: https://openbenchmarking.org/result/2310231-NE-EXTRATEST13.
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
nekRS
Input: Kershaw
nekRS
Input: TurboPipe Periodic
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
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
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
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
Timed Linux Kernel Compilation
Build: defconfig
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: 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
Dragonflydb
Clients Per Thread: 10 - Set To Get Ratio: 1:10
Dragonflydb
Clients Per Thread: 20 - Set To Get Ratio: 1:10
Dragonflydb
Clients Per Thread: 50 - Set To Get Ratio: 1:10
Dragonflydb
Clients Per Thread: 10 - Set To Get Ratio: 1:100
Dragonflydb
Clients Per Thread: 20 - Set To Get Ratio: 1:100
Dragonflydb
Clients Per Thread: 50 - Set To Get Ratio: 1:100
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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - 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 Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - 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: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-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, 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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - 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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - 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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
Stress-NG
Test: Hash
Stress-NG
Test: MMAP
Stress-NG
Test: NUMA
Stress-NG
Test: Pipe
Stress-NG
Test: Poll
Stress-NG
Test: Zlib
Stress-NG
Test: Futex
Stress-NG
Test: MEMFD
Stress-NG
Test: Mutex
Stress-NG
Test: Atomic
Stress-NG
Test: Crypto
Stress-NG
Test: Malloc
Stress-NG
Test: Cloning
Stress-NG
Test: Forking
Stress-NG
Test: AVL Tree
Stress-NG
Test: SENDFILE
Stress-NG
Test: CPU Cache
Stress-NG
Test: CPU Stress
Stress-NG
Test: Semaphores
Stress-NG
Test: Matrix Math
Stress-NG
Test: Vector Math
Stress-NG
Test: AVX-512 VNNI
Stress-NG
Test: Function Call
Stress-NG
Test: x86_64 RdRand
Stress-NG
Test: Floating Point
Stress-NG
Test: Matrix 3D Math
Stress-NG
Test: Memory Copying
Stress-NG
Test: Vector Shuffle
Stress-NG
Test: Mixed Scheduler
Stress-NG
Test: Socket Activity
Stress-NG
Test: Wide Vector Math
Stress-NG
Test: Context Switching
Stress-NG
Test: Fused Multiply-Add
Stress-NG
Test: Vector Floating Point
Stress-NG
Test: Glibc C String Functions
Stress-NG
Test: Glibc Qsort Data Sorting
Stress-NG
Test: System V Message Passing
NCNN
Target: CPU - Model: mobilenet
NCNN
Target: CPU-v2-v2 - Model: mobilenet-v2
NCNN
Target: CPU-v3-v3 - Model: mobilenet-v3
NCNN
Target: CPU - Model: shufflenet-v2
NCNN
Target: CPU - Model: mnasnet
NCNN
Target: CPU - Model: efficientnet-b0
NCNN
Target: CPU - Model: blazeface
NCNN
Target: CPU - Model: googlenet
NCNN
Target: CPU - Model: vgg16
NCNN
Target: CPU - Model: resnet18
NCNN
Target: CPU - Model: alexnet
NCNN
Target: CPU - Model: resnet50
NCNN
Target: CPU - Model: yolov4-tiny
NCNN
Target: CPU - Model: squeezenet_ssd
NCNN
Target: CPU - Model: regnety_400m
NCNN
Target: CPU - Model: vision_transformer
NCNN
Target: CPU - Model: FastestDet
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
Apache Cassandra
Test: Writes
Kripke
BRL-CAD
VGR Performance Metric
Stress-NG
Test: Pthread
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
Apache Hadoop
Operation: Create - Threads: 20 - Files: 100000
Apache Hadoop
Operation: Create - Threads: 20 - Files: 1000000
Apache Hadoop
Operation: Create - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Create - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Create - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Create - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Create - Threads: 500 - Files: 100000
Apache Hadoop
Operation: Create - Threads: 500 - Files: 1000000
Apache Hadoop
Operation: Open - Threads: 20 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 20 - Files: 1000000
Apache Hadoop
Operation: Open - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Open - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Open - Threads: 500 - Files: 100000
Apache Hadoop
Operation: Open - Threads: 500 - Files: 1000000
Apache Hadoop
Operation: Delete - Threads: 20 - Files: 100000
Apache Hadoop
Operation: Delete - Threads: 20 - Files: 1000000
Apache Hadoop
Operation: Delete - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Delete - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Delete - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Delete - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Delete - Threads: 500 - Files: 100000
Apache Hadoop
Operation: Delete - Threads: 500 - Files: 1000000
Apache Hadoop
Operation: File Status - Threads: 20 - Files: 100000
Apache Hadoop
Operation: File Status - Threads: 20 - Files: 1000000
Apache Hadoop
Operation: File Status - Threads: 50 - Files: 100000
Apache Hadoop
Operation: File Status - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: File Status - Threads: 100 - Files: 100000
Apache Hadoop
Operation: File Status - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: File Status - Threads: 500 - Files: 100000
Apache Hadoop
Operation: File Status - Threads: 500 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 20 - Files: 100000
Apache Hadoop
Operation: Rename - Threads: 20 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 50 - Files: 100000
Apache Hadoop
Operation: Rename - Threads: 50 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 100 - Files: 100000
Apache Hadoop
Operation: Rename - Threads: 100 - Files: 1000000
Apache Hadoop
Operation: Rename - Threads: 500 - Files: 100000
Apache Hadoop
Operation: Rename - Threads: 500 - 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_read_write - Threads: 128
TiDB Community Server
Test: oltp_read_write - Threads: 256
TiDB Community Server
Test: oltp_point_select - 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_point_select - Threads: 128
TiDB Community Server
Test: oltp_point_select - Threads: 256
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
Dragonflydb
Clients Per Thread: 60 - Set To Get Ratio: 1:10
Dragonflydb
Clients Per Thread: 60 - Set To Get Ratio: 1:100
Phoronix Test Suite v10.8.5