nov 2022 Suite
1.0.0
System
Test suite extracted from nov 2022.
pts/stream-1.3.4
Copy
Type: Copy
pts/stream-1.3.4
Scale
Type: Scale
pts/stream-1.3.4
Triad
Type: Triad
pts/stream-1.3.4
Add
Type: Add
pts/minibude-1.0.0
--deck ../data/bm1 --iterations 500
Implementation: OpenMP - Input Deck: BM1
pts/minibude-1.0.0
--deck ../data/bm2 --iterations 10
Implementation: OpenMP - Input Deck: BM2
pts/nekrs-1.0.0
turbPipePeriodic turbPipe.par
Input: TurboPipe Periodic
pts/openradioss-1.0.0
Bumper_Beam_AP_meshed_0000.rad Bumper_Beam_AP_meshed_0001.rad
Model: Bumper Beam
pts/openradioss-1.0.0
Cell_Phone_Drop_0000.rad Cell_Phone_Drop_0001.rad
Model: Cell Phone Drop Test
pts/openradioss-1.0.0
BIRD_WINDSHIELD_v1_0000.rad BIRD_WINDSHIELD_v1_0001.rad
Model: Bird Strike on Windshield
pts/openradioss-1.0.0
RUBBER_SEAL_IMPDISP_GEOM_0000.rad RUBBER_SEAL_IMPDISP_GEOM_0001.rad
Model: Rubber O-Ring Seal Installation
pts/openradioss-1.0.0
fsi_drop_container_0000.rad fsi_drop_container_0001.rad
Model: INIVOL and Fluid Structure Interaction Drop Container
pts/xmrig-1.1.0
--bench=1M
Variant: Monero - Hash Count: 1M
pts/xmrig-1.1.0
-a rx/wow --bench=1M
Variant: Wownero - Hash Count: 1M
pts/jpegxl-1.5.0
sample-4.png out.jxl -q 80 --num_reps 50
Input: PNG - Quality: 80
pts/jpegxl-1.5.0
sample-4.png out.jxl -q 90 --num_reps 40
Input: PNG - Quality: 90
pts/jpegxl-1.5.0
--lossless_jpeg=0 sample-photo-6000x4000.JPG out.jxl -q 80 --num_reps 50
Input: JPEG - Quality: 80
pts/jpegxl-1.5.0
--lossless_jpeg=0 sample-photo-6000x4000.JPG out.jxl -q 90 --num_reps 40
Input: JPEG - Quality: 90
pts/jpegxl-1.5.0
sample-4.png out.jxl -q 100 --num_reps 10
Input: PNG - Quality: 100
pts/jpegxl-1.5.0
--lossless_jpeg=0 sample-photo-6000x4000.JPG out.jxl -q 100 --num_reps 10
Input: JPEG - Quality: 100
pts/jpegxl-decode-1.5.0
--num_threads=1 --num_reps=100
CPU Threads: 1
pts/jpegxl-decode-1.5.0
--num_reps=200
CPU Threads: All
pts/avifenc-1.3.0
-s 0
Encoder Speed: 0
pts/avifenc-1.3.0
-s 2
Encoder Speed: 2
pts/avifenc-1.3.0
-s 6
Encoder Speed: 6
pts/avifenc-1.3.0
-s 6 -l
Encoder Speed: 6, Lossless
pts/avifenc-1.3.0
-s 10 -l
Encoder Speed: 10, Lossless
pts/encode-flac-1.8.1
WAV To FLAC
pts/ffmpeg-3.0.0
--encoder=libx264 live
Encoder: libx264 - Scenario: Live
pts/ffmpeg-3.0.0
--encoder=libx265 live
Encoder: libx265 - Scenario: Live
pts/ffmpeg-3.0.0
--encoder=libx264 upload
Encoder: libx264 - Scenario: Upload
pts/ffmpeg-3.0.0
--encoder=libx265 upload
Encoder: libx265 - Scenario: Upload
pts/ffmpeg-3.0.0
--encoder=libx264 platform
Encoder: libx264 - Scenario: Platform
pts/ffmpeg-3.0.0
--encoder=libx265 platform
Encoder: libx265 - Scenario: Platform
pts/ffmpeg-3.0.0
--encoder=libx264 vod
Encoder: libx264 - Scenario: Video On Demand
pts/ffmpeg-3.0.0
--encoder=libx265 vod
Encoder: libx265 - Scenario: Video On Demand
pts/deepsparse-1.0.1
zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario async
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario sync
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
pts/deepsparse-1.0.1
zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario async
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario sync
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
pts/deepsparse-1.0.1
zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario async
Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario sync
Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream
pts/deepsparse-1.0.1
zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario async
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario sync
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
pts/deepsparse-1.0.1
zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario async
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario sync
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
pts/deepsparse-1.0.1
zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario async
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario sync
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
pts/deepsparse-1.0.1
zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario async
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.0.1
zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario sync
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
pts/memtier-benchmark-1.4.1
-P redis -c 50 --ratio=10:1
Protocol: Redis - Clients: 50 - Set To Get Ratio: 10:1
pts/memtier-benchmark-1.4.1
-P redis -c 50 --ratio=1:10
Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10
pts/memtier-benchmark-1.4.1
-P redis -c 100 --ratio=10:1
Protocol: Redis - Clients: 100 - Set To Get Ratio: 10:1
pts/memtier-benchmark-1.4.1
-P redis -c 100 --ratio=1:10
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10
pts/memtier-benchmark-1.4.1
-P redis -c 500 --ratio=10:1
Protocol: Redis - Clients: 500 - Set To Get Ratio: 10:1
pts/memtier-benchmark-1.4.1
-P redis -c 500 --ratio=1:10
Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10
pts/stress-ng-1.6.0
--mmap -1
Test: MMAP
pts/stress-ng-1.6.0
--numa -1
Test: NUMA
pts/stress-ng-1.6.0
--futex -1
Test: Futex
pts/stress-ng-1.6.0
--memfd -1
Test: MEMFD
pts/stress-ng-1.6.0
--mutex -1
Test: Mutex
pts/stress-ng-1.6.0
--atomic -1
Test: Atomic
pts/stress-ng-1.6.0
--crypt -1
Test: Crypto
pts/stress-ng-1.6.0
--malloc -1
Test: Malloc
pts/stress-ng-1.6.0
--fork -1
Test: Forking
pts/stress-ng-1.6.0
--io-uring -1
Test: IO_uring
pts/stress-ng-1.6.0
--sendfile -1
Test: SENDFILE
pts/stress-ng-1.6.0
--cache -1
Test: CPU Cache
pts/stress-ng-1.6.0
--cpu -1 --cpu-method all
Test: CPU Stress
pts/stress-ng-1.6.0
--sem -1
Test: Semaphores
pts/stress-ng-1.6.0
--matrix -1
Test: Matrix Math
pts/stress-ng-1.6.0
--vecmath -1
Test: Vector Math
pts/stress-ng-1.6.0
--rdrand -1
Test: x86_64 RdRand
pts/stress-ng-1.6.0
--memcpy -1
Test: Memory Copying
pts/stress-ng-1.6.0
--sock -1
Test: Socket Activity
pts/stress-ng-1.6.0
--switch -1
Test: Context Switching
pts/stress-ng-1.6.0
--str -1
Test: Glibc C String Functions
pts/stress-ng-1.6.0
--qsort -1
Test: Glibc Qsort Data Sorting
pts/stress-ng-1.6.0
--msg -1
Test: System V Message Passing
pts/nginx-3.0.0
-c 1
Connections: 1
pts/nginx-3.0.0
-c 20
Connections: 20
pts/nginx-3.0.0
-c 100
Connections: 100
pts/nginx-3.0.0
-c 200
Connections: 200
pts/nginx-3.0.0
-c 500
Connections: 500
pts/nginx-3.0.0
-c 1000
Connections: 1000
pts/nginx-3.0.0
-c 4000
Connections: 4000
pts/encodec-1.0.1
-b 3
Target Bandwidth: 3 kbps
pts/encodec-1.0.1
-b 6
Target Bandwidth: 6 kbps
pts/encodec-1.0.1
-b 24
Target Bandwidth: 24 kbps
pts/encodec-1.0.1
-b 1.5
Target Bandwidth: 1.5 kbps