Xeon Gold Cascade Lake Refresh LTS Linux Benchmarks Suite
1.0.0
System
Test suite extracted from Xeon Gold Cascade Lake Refresh LTS Linux Benchmarks.
pts/compress-7zip-1.10.0
Test: Compression Rating
pts/compress-7zip-1.10.0
Test: Decompression Rating
pts/aircrack-ng-1.3.0
pts/aom-av1-3.5.0
--cpu-used=6 Bosphorus_3840x2160.y4m
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=8 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=9 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=10 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K
pts/astcenc-1.4.0
-fast -repeats 120
Preset: Fast
pts/astcenc-1.4.0
-medium -repeats 20
Preset: Medium
pts/astcenc-1.4.0
-thorough -repeats 10
Preset: Thorough
pts/astcenc-1.4.0
-exhaustive -repeats 2
Preset: Exhaustive
pts/blender-3.4.0
-b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: BMW27 - Compute: CPU-Only
pts/blender-3.4.0
-b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: Classroom - Compute: CPU-Only
pts/blender-3.4.0
-b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: Fishy Cat - Compute: CPU-Only
pts/blender-3.4.0
-b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: Barbershop - Compute: CPU-Only
pts/blender-3.4.0
-b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU
Blend File: Pabellon Barcelona - Compute: CPU-Only
pts/brl-cad-1.3.0
VGR Performance Metric
pts/blosc-1.2.0
blosclz shuffle
Test: blosclz shuffle
pts/blosc-1.2.0
blosclz bitshuffle
Test: blosclz bitshuffle
pts/clickhouse-1.1.0
100M Rows Web Analytics Dataset, First Run / Cold Cache
pts/clickhouse-1.1.0
100M Rows Web Analytics Dataset, Second Run
pts/clickhouse-1.1.0
100M Rows Web Analytics Dataset, Third Run
pts/cpuminer-opt-1.6.0
-a m7m
Algorithm: Magi
pts/cpuminer-opt-1.6.0
-a x25x
Algorithm: x25x
pts/cpuminer-opt-1.6.0
-a scrypt
Algorithm: scrypt
pts/cpuminer-opt-1.6.0
-a deep
Algorithm: Deepcoin
pts/cpuminer-opt-1.6.0
-a minotaur
Algorithm: Ringcoin
pts/cpuminer-opt-1.6.0
-a blake2s
Algorithm: Blake-2 S
pts/cpuminer-opt-1.6.0
-a allium
Algorithm: Garlicoin
pts/cpuminer-opt-1.6.0
-a skein
Algorithm: Skeincoin
pts/cpuminer-opt-1.6.0
-a myr-gr
Algorithm: Myriad-Groestl
pts/cpuminer-opt-1.6.0
-a lbry
Algorithm: LBC, LBRY Credits
pts/cpuminer-opt-1.6.0
-a sha256q
Algorithm: Quad SHA-256, Pyrite
pts/cpuminer-opt-1.6.0
-a sha256t
Algorithm: Triple SHA-256, Onecoin
pts/ctx-clock-1.0.0
Context Switch Time
pts/dragonflydb-1.0.0
-c 50 --ratio=1:1
Clients: 50 - Set To Get Ratio: 1:1
pts/dragonflydb-1.0.0
-c 50 --ratio=1:5
Clients: 50 - Set To Get Ratio: 1:5
pts/dragonflydb-1.0.0
-c 50 --ratio=5:1
Clients: 50 - Set To Get Ratio: 5:1
pts/dragonflydb-1.0.0
-c 200 --ratio=1:1
Clients: 200 - Set To Get Ratio: 1:1
pts/dragonflydb-1.0.0
-c 200 --ratio=1:5
Clients: 200 - Set To Get Ratio: 1:5
pts/dragonflydb-1.0.0
-c 200 --ratio=5:1
Clients: 200 - Set To Get Ratio: 5:1
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
pts/rocksdb-1.3.0
--benchmarks="fillrandom"
Test: Random Fill
pts/rocksdb-1.3.0
--benchmarks="readrandom"
Test: Random Read
pts/rocksdb-1.3.0
--benchmarks="updaterandom"
Test: Update Random
pts/rocksdb-1.3.0
--benchmarks="fillseq"
Test: Sequential Fill
pts/rocksdb-1.3.0
--benchmarks="fillsync"
Test: Random Fill Sync
pts/rocksdb-1.3.0
--benchmarks="readwhilewriting"
Test: Read While Writing
pts/rocksdb-1.3.0
--benchmarks="readrandomwriterandom"
Test: Read Random Write Random
pts/encode-flac-1.8.1
WAV To FLAC
pts/graphics-magick-2.1.0
-swirl 90
Operation: Swirl
pts/graphics-magick-2.1.0
-rotate 90
Operation: Rotate
pts/graphics-magick-2.1.0
-sharpen 0x2.0
Operation: Sharpen
pts/graphics-magick-2.1.0
-enhance
Operation: Enhanced
pts/graphics-magick-2.1.0
-resize 50%
Operation: Resizing
pts/graphics-magick-2.1.0
-operator all Noise-Gaussian 30%
Operation: Noise-Gaussian
pts/graphics-magick-2.1.0
-colorspace HWB
Operation: HWB Color Space
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/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/lammps-1.4.0
benchmark_20k_atoms.in
Model: 20k Atoms
pts/lammps-1.4.0
in.rhodo
Model: Rhodopsin Protein
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/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/mnn-2.1.0
Model: nasnet
pts/mnn-2.1.0
Model: mobilenetV3
pts/mnn-2.1.0
Model: squeezenetv1.1
pts/mnn-2.1.0
Model: resnet-v2-50
pts/mnn-2.1.0
Model: SqueezeNetV1.0
pts/mnn-2.1.0
Model: MobileNetV2_224
pts/mnn-2.1.0
Model: mobilenet-v1-1.0
pts/mnn-2.1.0
Model: inception-v3
pts/natron-1.1.0
Natron_2.3.12_Spaceship/Natron_project/Spaceship_Natron.ntp
Input: Spaceship
pts/ncnn-1.4.0
-1
Target: CPU - Model: mobilenet
pts/ncnn-1.4.0
-1
Target: CPU-v2-v2 - Model: mobilenet-v2
pts/ncnn-1.4.0
-1
Target: CPU-v3-v3 - Model: mobilenet-v3
pts/ncnn-1.4.0
-1
Target: CPU - Model: shufflenet-v2
pts/ncnn-1.4.0
-1
Target: CPU - Model: mnasnet
pts/ncnn-1.4.0
-1
Target: CPU - Model: efficientnet-b0
pts/ncnn-1.4.0
-1
Target: CPU - Model: blazeface
pts/ncnn-1.4.0
-1
Target: CPU - Model: googlenet
pts/ncnn-1.4.0
-1
Target: CPU - Model: vgg16
pts/ncnn-1.4.0
-1
Target: CPU - Model: resnet18
pts/ncnn-1.4.0
-1
Target: CPU - Model: alexnet
pts/ncnn-1.4.0
-1
Target: CPU - Model: resnet50
pts/ncnn-1.4.0
-1
Target: CPU - Model: yolov4-tiny
pts/ncnn-1.4.0
-1
Target: CPU - Model: squeezenet_ssd
pts/ncnn-1.4.0
-1
Target: CPU - Model: regnety_400m
pts/ncnn-1.4.0
-1
Target: CPU - Model: vision_transformer
pts/ncnn-1.4.0
-1
Target: CPU - Model: FastestDet
pts/nekrs-1.0.0
turbPipePeriodic turbPipe.par
Input: TurboPipe Periodic
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/numenta-nab-1.1.1
-d knncad
Detector: KNN CAD
pts/numenta-nab-1.1.1
-d relativeEntropy
Detector: Relative Entropy
pts/numenta-nab-1.1.1
-d windowedGaussian
Detector: Windowed Gaussian
pts/numenta-nab-1.1.1
-d earthgeckoSkyline
Detector: Earthgecko Skyline
pts/numenta-nab-1.1.1
-d bayesChangePt
Detector: Bayesian Changepoint
pts/numenta-nab-1.1.1
-d contextOSE
Detector: Contextual Anomaly Detector OSE
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
pts/openfoam-1.2.0
incompressible/simpleFoam/drivaerFastback/ -m S
Input: drivaerFastback, Small Mesh Size - Mesh Time
pts/openfoam-1.2.0
incompressible/simpleFoam/drivaerFastback/ -m S
Input: drivaerFastback, Small Mesh Size - Execution Time
pts/openfoam-1.2.0
incompressible/simpleFoam/drivaerFastback/ -m M
Input: drivaerFastback, Medium Mesh Size - Mesh Time
pts/openfoam-1.2.0
incompressible/simpleFoam/drivaerFastback/ -m M
Input: drivaerFastback, Medium Mesh Size - Execution Time
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/openvino-1.1.0
-m models/intel/face-detection-0206/FP16/face-detection-0206.xml -d CPU
Model: Face Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/person-detection-0106/FP16/person-detection-0106.xml -d CPU
Model: Person Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/person-detection-0106/FP32/person-detection-0106.xml -d CPU
Model: Person Detection FP32 - Device: CPU
pts/openvino-1.1.0
-m models/intel/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU
Model: Vehicle Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/face-detection-0206/FP16-INT8/face-detection-0206.xml -d CPU
Model: Face Detection FP16-INT8 - Device: CPU
pts/openvino-1.1.0
-m models/intel/vehicle-detection-0202/FP16-INT8/vehicle-detection-0202.xml -d CPU
Model: Vehicle Detection FP16-INT8 - Device: CPU
pts/openvino-1.1.0
-m models/intel/weld-porosity-detection-0001/FP16/weld-porosity-detection-0001.xml -d CPU
Model: Weld Porosity Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/machine-translation-nar-en-de-0002/FP16/machine-translation-nar-en-de-0002.xml -d CPU
Model: Machine Translation EN To DE FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/weld-porosity-detection-0001/FP16-INT8/weld-porosity-detection-0001.xml -d CPU
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
pts/openvino-1.1.0
-m models/intel/person-vehicle-bike-detection-2004/FP16/person-vehicle-bike-detection-2004.xml -d CPU
Model: Person Vehicle Bike Detection FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013.xml -d CPU
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
pts/openvino-1.1.0
-m models/intel/age-gender-recognition-retail-0013/FP16-INT8/age-gender-recognition-retail-0013.xml -d CPU
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
pts/ospray-studio-1.1.0
--cameras 1 1 --resolution 3840 2160 --spp 1 --renderer pathtracer
Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 2 2 --resolution 3840 2160 --spp 1 --renderer pathtracer
Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 3 3 --resolution 3840 2160 --spp 1 --renderer pathtracer
Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 1 1 --resolution 3840 2160 --spp 16 --renderer pathtracer
Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 1 1 --resolution 3840 2160 --spp 32 --renderer pathtracer
Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 2 2 --resolution 3840 2160 --spp 16 --renderer pathtracer
Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 2 2 --resolution 3840 2160 --spp 32 --renderer pathtracer
Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 3 3 --resolution 3840 2160 --spp 16 --renderer pathtracer
Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 3 3 --resolution 3840 2160 --spp 32 --renderer pathtracer
Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 1 1 --resolution 1920 1080 --spp 1 --renderer pathtracer
Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 2 2 --resolution 1920 1080 --spp 1 --renderer pathtracer
Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 3 3 --resolution 1920 1080 --spp 1 --renderer pathtracer
Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 1 1 --resolution 1920 1080 --spp 16 --renderer pathtracer
Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 1 1 --resolution 1920 1080 --spp 32 --renderer pathtracer
Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 2 2 --resolution 1920 1080 --spp 16 --renderer pathtracer
Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 2 2 --resolution 1920 1080 --spp 32 --renderer pathtracer
Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 3 3 --resolution 1920 1080 --spp 16 --renderer pathtracer
Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer
pts/ospray-studio-1.1.0
--cameras 3 3 --resolution 1920 1080 --spp 32 --renderer pathtracer
Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer
pts/pgbench-1.12.0
-s 100 -c 100 -S
Scaling Factor: 100 - Clients: 100 - Mode: Read Only
pts/pgbench-1.12.0
-s 100 -c 100 -S
Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency
pts/pgbench-1.12.0
-s 100 -c 250 -S
Scaling Factor: 100 - Clients: 250 - Mode: Read Only
pts/pgbench-1.12.0
-s 100 -c 250 -S
Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency
pts/pgbench-1.12.0
-s 100 -c 500 -S
Scaling Factor: 100 - Clients: 500 - Mode: Read Only
pts/pgbench-1.12.0
-s 100 -c 500 -S
Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency
pts/pgbench-1.12.0
-s 100 -c 100
Scaling Factor: 100 - Clients: 100 - Mode: Read Write
pts/pgbench-1.12.0
-s 100 -c 100
Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency
pts/pgbench-1.12.0
-s 100 -c 250
Scaling Factor: 100 - Clients: 250 - Mode: Read Write
pts/pgbench-1.12.0
-s 100 -c 250
Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency
pts/pgbench-1.12.0
-s 100 -c 500
Scaling Factor: 100 - Clients: 500 - Mode: Read Write
pts/pgbench-1.12.0
-s 100 -c 500
Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency
pts/primesieve-1.9.0
1e12
Length: 1e12
pts/primesieve-1.9.0
1e13
Length: 1e13
pts/spacy-1.0.0
Model: en_core_web_lg
pts/spacy-1.0.0
Model: en_core_web_trf
pts/srsran-1.2.0
lib/src/phy/dft/test/ofdm_test -N 2048 -n 100 -r 500000
Test: OFDM_Test
pts/srsran-1.2.0
lib/test/phy/phy_dl_test -p 100 -s 20000 -m 28 -t 4
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
pts/srsran-1.2.0
lib/test/phy/phy_dl_test -p 100 -s 20000 -m 28 -t 1
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
pts/srsran-1.2.0
lib/test/phy/phy_dl_test -p 100 -s 20000 -m 27 -t 4 -q
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
pts/srsran-1.2.0
lib/test/phy/phy_dl_test -p 100 -s 20000 -m 27 -t 1 -q
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
pts/srsran-1.2.0
lib/test/phy/phy_dl_nr_test -P 52 -p 52 -m 28 -n 20000
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
pts/stargate-1.1.0
44100 512
Sample Rate: 44100 - Buffer Size: 512
pts/stargate-1.1.0
96000 512
Sample Rate: 96000 - Buffer Size: 512
pts/stargate-1.1.0
192000 512
Sample Rate: 192000 - Buffer Size: 512
pts/stargate-1.1.0
44100 1024
Sample Rate: 44100 - Buffer Size: 1024
pts/stargate-1.1.0
48000 512
Sample Rate: 480000 - Buffer Size: 512
pts/stargate-1.1.0
96000 1024
Sample Rate: 96000 - Buffer Size: 1024
pts/stargate-1.1.0
192000 1024
Sample Rate: 192000 - Buffer Size: 1024
pts/stargate-1.1.0
48000 1024
Sample Rate: 480000 - Buffer Size: 1024
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/svt-av1-2.7.0
--preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 4 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 8 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 12 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160
Encoder Mode: Preset 13 - Input: Bosphorus 4K
pts/svt-av1-2.7.0
--preset 4 -n 160 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
pts/svt-av1-2.7.0
--preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
pts/svt-av1-2.7.0
--preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
pts/svt-av1-2.7.0
--preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
pts/tensorflow-2.0.0
--device cpu --batch_size=16 --model=alexnet
Device: CPU - Batch Size: 16 - Model: AlexNet
pts/tensorflow-2.0.0
--device cpu --batch_size=32 --model=alexnet
Device: CPU - Batch Size: 32 - Model: AlexNet
pts/tensorflow-2.0.0
--device cpu --batch_size=64 --model=alexnet
Device: CPU - Batch Size: 64 - Model: AlexNet
pts/tensorflow-2.0.0
--device cpu --batch_size=256 --model=alexnet
Device: CPU - Batch Size: 256 - Model: AlexNet
pts/tensorflow-2.0.0
--device cpu --batch_size=16 --model=googlenet
Device: CPU - Batch Size: 16 - Model: GoogLeNet
pts/tensorflow-2.0.0
--device cpu --batch_size=16 --model=resnet50
Device: CPU - Batch Size: 16 - Model: ResNet-50
pts/tensorflow-2.0.0
--device cpu --batch_size=32 --model=googlenet
Device: CPU - Batch Size: 32 - Model: GoogLeNet
pts/tensorflow-2.0.0
--device cpu --batch_size=32 --model=resnet50
Device: CPU - Batch Size: 32 - Model: ResNet-50
pts/tensorflow-2.0.0
--device cpu --batch_size=64 --model=googlenet
Device: CPU - Batch Size: 64 - Model: GoogLeNet
pts/tensorflow-2.0.0
--device cpu --batch_size=64 --model=resnet50
Device: CPU - Batch Size: 64 - Model: ResNet-50
pts/tensorflow-2.0.0
--device cpu --batch_size=256 --model=googlenet
Device: CPU - Batch Size: 256 - Model: GoogLeNet
pts/tensorflow-2.0.0
--device cpu --batch_size=256 --model=resnet50
Device: CPU - Batch Size: 256 - Model: ResNet-50
pts/build-python-1.0.0
Build Configuration: Default
pts/build-python-1.0.0
--enable-optimizations --with-lto
Build Configuration: Released Build, PGO + LTO Optimized
pts/build-erlang-1.2.0
Time To Compile
pts/build-godot-1.0.0
Time To Compile
pts/build-linux-kernel-1.15.0
defconfig
Build: defconfig
pts/build-linux-kernel-1.15.0
allmodconfig
Build: allmodconfig
pts/build-nodejs-1.2.0
Time To Compile
pts/build-php-1.6.0
Time To Compile
pts/webp-1.2.0
Encode Settings: Default
pts/webp-1.2.0
-q 100
Encode Settings: Quality 100
pts/webp-1.2.0
-q 100 -lossless
Encode Settings: Quality 100, Lossless
pts/webp-1.2.0
-q 100 -m 6
Encode Settings: Quality 100, Highest Compression
pts/webp-1.2.0
-q 100 -lossless -m 6
Encode Settings: Quality 100, Lossless, Highest Compression
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/y-cruncher-1.2.0
1b
Pi Digits To Calculate: 1B
pts/y-cruncher-1.2.0
500m
Pi Digits To Calculate: 500M