tgls

Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2311135-PTS-TGLS547809
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AV1 2 Tests
C++ Boost Tests 3 Tests
Timed Code Compilation 3 Tests
C/C++ Compiler Tests 2 Tests
CPU Massive 8 Tests
Creator Workloads 11 Tests
Encoding 4 Tests
Game Development 2 Tests
HPC - High Performance Computing 7 Tests
Java Tests 3 Tests
Machine Learning 4 Tests
Multi-Core 15 Tests
Intel oneAPI 6 Tests
OpenMPI Tests 3 Tests
Programmer / Developer System Benchmarks 4 Tests
Python Tests 5 Tests
Scientific Computing 2 Tests
Server CPU Tests 6 Tests
Video Encoding 4 Tests

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November 12 2023
  8 Hours, 30 Minutes
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November 12 2023
  21 Hours, 56 Minutes
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November 13 2023
  21 Hours, 46 Minutes
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tgls Suite 1.0.0 System Test suite extracted from tgls. pts/stress-ng-1.11.0 --hash -1 --no-rand-seed Test: Hash pts/stress-ng-1.11.0 --mmap -1 --no-rand-seed Test: MMAP pts/stress-ng-1.11.0 --numa -1 --no-rand-seed Test: NUMA pts/stress-ng-1.11.0 --pipe -1 --no-rand-seed Test: Pipe pts/stress-ng-1.11.0 --poll -1 --no-rand-seed Test: Poll pts/stress-ng-1.11.0 --zlib -1 --no-rand-seed Test: Zlib pts/stress-ng-1.11.0 --futex -1 --no-rand-seed Test: Futex pts/stress-ng-1.11.0 --memfd -1 --no-rand-seed Test: MEMFD pts/stress-ng-1.11.0 --mutex -1 --no-rand-seed Test: Mutex pts/stress-ng-1.11.0 --atomic -1 --no-rand-seed Test: Atomic pts/stress-ng-1.11.0 --crypt -1 --no-rand-seed Test: Crypto pts/stress-ng-1.11.0 --malloc -1 --no-rand-seed Test: Malloc pts/stress-ng-1.11.0 --clone -1 --no-rand-seed Test: Cloning pts/stress-ng-1.11.0 --fork -1 --no-rand-seed Test: Forking pts/stress-ng-1.11.0 --pthread -1 --no-rand-seed Test: Pthread pts/stress-ng-1.11.0 --tree -1 --tree-method avl --no-rand-seed Test: AVL Tree pts/stress-ng-1.11.0 --io-uring -1 --no-rand-seed Test: IO_uring pts/stress-ng-1.11.0 --sendfile -1 --no-rand-seed Test: SENDFILE pts/stress-ng-1.11.0 --cache -1 --no-rand-seed Test: CPU Cache pts/stress-ng-1.11.0 --cpu -1 --cpu-method all --no-rand-seed Test: CPU Stress pts/stress-ng-1.11.0 --sem -1 --no-rand-seed Test: Semaphores pts/rabbitmq-1.1.1 --queue-pattern 'perf-test-%d' --queue-pattern-from 1 --queue-pattern-to 10 --producers 100 --consumers 100 -s 8000 Scenario: 10 Queues, 100 Producers, 100 Consumers pts/stress-ng-1.11.0 --matrix -1 --no-rand-seed Test: Matrix Math pts/stress-ng-1.11.0 --vecmath -1 --no-rand-seed Test: Vector Math pts/stress-ng-1.11.0 --vnni -1 Test: AVX-512 VNNI pts/stress-ng-1.11.0 --funccall -1 --no-rand-seed Test: Function Call pts/stress-ng-1.11.0 --rdrand -1 --no-rand-seed Test: x86_64 RdRand pts/stress-ng-1.11.0 --fp -1 --no-rand-seed Test: Floating Point pts/stress-ng-1.11.0 --matrix-3d -1 --no-rand-seed Test: Matrix 3D Math pts/stress-ng-1.11.0 --memcpy -1 --no-rand-seed Test: Memory Copying pts/stress-ng-1.11.0 --vecshuf -1 --no-rand-seed Test: Vector Shuffle pts/stress-ng-1.11.0 --schedmix -1 Test: Mixed Scheduler pts/stress-ng-1.11.0 --sock -1 --no-rand-seed --sock-zerocopy Test: Socket Activity pts/stress-ng-1.11.0 --vecwide -1 --no-rand-seed Test: Wide Vector Math pts/stress-ng-1.11.0 --switch -1 --no-rand-seed Test: Context Switching pts/stress-ng-1.11.0 --fma -1 --no-rand-seed Test: Fused Multiply-Add pts/stress-ng-1.11.0 --vecfp -1 --no-rand-seed Test: Vector Floating Point pts/stress-ng-1.11.0 --str -1 --no-rand-seed Test: Glibc C String Functions pts/stress-ng-1.11.0 --qsort -1 --no-rand-seed Test: Glibc Qsort Data Sorting pts/stress-ng-1.11.0 --msg -1 --no-rand-seed Test: System V Message Passing pts/dacapobench-1.1.0 jython Java Test: Jython pts/dacapobench-1.1.0 eclipse Java Test: Eclipse pts/dacapobench-1.1.0 graphchi Java Test: GraphChi pts/dacapobench-1.1.0 tradesoap Java Test: Tradesoap pts/dacapobench-1.1.0 tradebeans Java Test: Tradebeans pts/dacapobench-1.1.0 spring Java Test: Spring Boot pts/dacapobench-1.1.0 kafka Java Test: Apache Kafka pts/dacapobench-1.1.0 tomcat Java Test: Apache Tomcat pts/dacapobench-1.1.0 jme Java Test: jMonkeyEngine pts/easywave-1.0.0 -grid examples/e2Asean.grd -source examples/BengkuluSept2007.flt -time 240 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 pts/easywave-1.0.0 -grid examples/e2Asean.grd -source examples/BengkuluSept2007.flt -time 1200 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 pts/dacapobench-1.1.0 cassandra Java Test: Apache Cassandra pts/dacapobench-1.1.0 xalan Java Test: Apache Xalan XSLT pts/dacapobench-1.1.0 batik Java Test: Batik SVG Toolkit pts/dacapobench-1.1.0 h2 Java Test: H2 Database Engine pts/dacapobench-1.1.0 fop Java Test: FOP Print Formatter pts/dacapobench-1.1.0 pmd Java Test: PMD Source Code Analyzer pts/dacapobench-1.1.0 luindex Java Test: Apache Lucene Search Index pts/dacapobench-1.1.0 lusearch Java Test: Apache Lucene Search Engine pts/dacapobench-1.1.0 avrora Java Test: Avrora AVR Simulation Framework pts/dacapobench-1.1.0 biojava Java Test: BioJava Biological Data Framework pts/dacapobench-1.1.0 zxing Java Test: Zxing 1D/2D Barcode Image Processing pts/dacapobench-1.1.0 h2o Java Test: H2O In-Memory Platform For Machine Learning pts/brl-cad-1.5.0 VGR Performance Metric pts/quantlib-1.2.0 --mp Configuration: Multi-Threaded pts/quantlib-1.2.0 Configuration: Single-Threaded pts/openradioss-1.1.1 Cell_Phone_Drop_0000.rad Cell_Phone_Drop_0001.rad Model: Cell Phone Drop Test pts/openradioss-1.1.1 BIRD_WINDSHIELD_v1_0000.rad BIRD_WINDSHIELD_v1_0001.rad Model: Bird Strike on Windshield pts/openradioss-1.1.1 RUBBER_SEAL_IMPDISP_GEOM_0000.rad RUBBER_SEAL_IMPDISP_GEOM_0001.rad Model: Rubber O-Ring Seal Installation pts/cloverleaf-1.2.0 clover_bm Input: clover_bm pts/cloverleaf-1.2.0 clover_bm64_short Input: clover_bm64_short pts/deepsparse-1.5.2 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-1.5.2 zoo:nlp/sentiment_analysis/oberta-base/pytorch/huggingface/sst2/pruned90_quant-none --input_shapes='[1,128]' --scenario async Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 zoo:nlp/sentiment_analysis/bert-base/pytorch/huggingface/sst2/12layer_pruned90-none --scenario async Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 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-1.5.2 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario async Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/pruned95_uniform_quant-none --scenario async Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario async Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 zoo:nlp/question_answering/obert-large/pytorch/huggingface/squad/base-none --input_shapes='[1,128]' --scenario async Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 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-1.5.2 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/pruned85-none --scenario async Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 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-1.5.2 zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/pruned90-none --scenario async Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 zoo:nlp/question_answering/obert-large/pytorch/huggingface/squad/pruned97_quant-none --input_shapes='[1,128]' --scenario async Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --input_shapes='[1,128]' --scenario async Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.5.2 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/ncnn-1.5.0 -1 Target: CPU - Model: mobilenet pts/ncnn-1.5.0 -1 Target: CPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.5.0 -1 Target: CPU-v3-v3 - Model: mobilenet-v3 pts/ncnn-1.5.0 -1 Target: CPU - Model: shufflenet-v2 pts/ncnn-1.5.0 -1 Target: CPU - Model: mnasnet pts/ncnn-1.5.0 -1 Target: CPU - Model: efficientnet-b0 pts/ncnn-1.5.0 -1 Target: CPU - Model: blazeface pts/ncnn-1.5.0 -1 Target: CPU - Model: googlenet pts/ncnn-1.5.0 -1 Target: CPU - Model: vgg16 pts/ncnn-1.5.0 -1 Target: CPU - Model: resnet18 pts/ncnn-1.5.0 -1 Target: CPU - Model: alexnet pts/ncnn-1.5.0 -1 Target: CPU - Model: resnet50 pts/ncnn-1.5.0 -1 Target: CPU - Model: yolov4-tiny pts/rabbitmq-1.1.1 -x 2 -y 4 -u "throughput-test-2" -a --id "test 2" -s 8000 Scenario: Simple 2 Publishers + 4 Consumers pts/ncnn-1.5.0 -1 Target: CPU - Model: squeezenet_ssd pts/ncnn-1.5.0 -1 Target: CPU - Model: regnety_400m pts/ncnn-1.5.0 -1 Target: CPU - Model: vision_transformer pts/ncnn-1.5.0 -1 Target: CPU - Model: FastestDet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: mobilenet pts/ncnn-1.5.0 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.5.0 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: shufflenet-v2 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: mnasnet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: efficientnet-b0 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: blazeface pts/ncnn-1.5.0 Target: Vulkan GPU - Model: googlenet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: vgg16 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: resnet18 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: alexnet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: resnet50 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: yolov4-tiny pts/ncnn-1.5.0 Target: Vulkan GPU - Model: squeezenet_ssd pts/ncnn-1.5.0 Target: Vulkan GPU - Model: regnety_400m pts/ncnn-1.5.0 Target: Vulkan GPU - Model: vision_transformer pts/ncnn-1.5.0 Target: Vulkan GPU - Model: FastestDet pts/onednn-3.3.0 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/onednn-3.3.0 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/onednn-3.3.0 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.3.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.3.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/onednn-3.3.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/rabbitmq-1.1.1 --queue-pattern 'perf-test-%d' --queue-pattern-from 1 --queue-pattern-to 200 --producers 400 --consumers 400 -s 8000 Scenario: 200 Queues, 400 Producers, 400 Consumers pts/rabbitmq-1.1.1 --queue-pattern 'perf-test-%d' --queue-pattern-from 1 --queue-pattern-to 120 --producers 400 --consumers 400 -s 8000 Scenario: 120 Queues, 400 Producers, 400 Consumers pts/onednn-3.3.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/onednn-3.3.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/onednn-3.3.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-3.3.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.3.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.3.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.3.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.3.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.3.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/openvino-1.4.0 -m models/intel/face-detection-0206/FP16/face-detection-0206.xml -d CPU Model: Face Detection FP16 - Device: CPU pts/openvino-1.4.0 -m models/intel/person-detection-0303/FP16/person-detection-0303.xml -d CPU Model: Person Detection FP16 - Device: CPU pts/openvino-1.4.0 -m models/intel/person-detection-0303/FP32/person-detection-0303.xml -d CPU Model: Person Detection FP32 - Device: CPU pts/openvino-1.4.0 -m models/intel/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection FP16 - Device: CPU pts/openvino-1.4.0 -m models/intel/face-detection-0206/FP16-INT8/face-detection-0206.xml -d CPU Model: Face Detection FP16-INT8 - Device: CPU pts/openvino-1.4.0 -m models/intel/face-detection-retail-0005/FP16/face-detection-retail-0005.xml -d CPU Model: Face Detection Retail FP16 - Device: CPU pts/openvino-1.4.0 -m models/intel/road-segmentation-adas-0001/FP16/road-segmentation-adas-0001.xml -d CPU Model: Road Segmentation ADAS FP16 - Device: CPU pts/openvino-1.4.0 -m models/intel/vehicle-detection-0202/FP16-INT8/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection FP16-INT8 - Device: CPU pts/openvino-1.4.0 -m models/intel/weld-porosity-detection-0001/FP16/weld-porosity-detection-0001.xml -d CPU Model: Weld Porosity Detection FP16 - Device: CPU pts/openvino-1.4.0 -m models/intel/face-detection-retail-0005/FP16-INT8/face-detection-retail-0005.xml -d CPU Model: Face Detection Retail FP16-INT8 - Device: CPU pts/openvino-1.4.0 -m models/intel/road-segmentation-adas-0001/FP16-INT8/road-segmentation-adas-0001.xml -d CPU Model: Road Segmentation ADAS FP16-INT8 - Device: CPU pts/openvino-1.4.0 -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-1.4.0 -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/rabbitmq-1.1.1 --queue-pattern 'perf-test-%d' --queue-pattern-from 1 --queue-pattern-to 60 --producers 100 --consumers 100 -s 8000 Scenario: 60 Queues, 100 Producers, 100 Consumers pts/openvino-1.4.0 -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-1.4.0 -m models/intel/handwritten-english-recognition-0001/FP16/handwritten-english-recognition-0001.xml -d CPU Model: Handwritten English Recognition FP16 - Device: CPU pts/openvino-1.4.0 -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-1.4.0 -m models/intel/handwritten-english-recognition-0001/FP16-INT8/handwritten-english-recognition-0001.xml -d CPU Model: Handwritten English Recognition FP16-INT8 - Device: CPU pts/openvino-1.4.0 -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/qmcpack-1.7.0 tests/molecules/H4_ae optm-linear-linemin.xml Input: H4_ae pts/qmcpack-1.7.0 tests/molecules/Li2_STO_ae Li2.STO.long.in.xml Input: Li2_STO_ae pts/qmcpack-1.7.0 tests/molecules/LiH_ae_MSD vmc_long_opt_CI.in.xml Input: LiH_ae_MSD pts/qmcpack-1.7.0 build/examples/molecules/H2O/example_H2O-1-1 simple-H2O.xml Input: simple-H2O pts/qmcpack-1.7.0 tests/molecules/O_ae_pyscf_UHF vmc_long_noj.in.xml Input: O_ae_pyscf_UHF pts/qmcpack-1.7.0 tests/molecules/FeCO6_b3lyp_gms vmc_long_noj.in.xml Input: FeCO6_b3lyp_gms pts/build-ffmpeg-6.1.0 Time To Compile pts/cpuminer-opt-1.7.0 -a m7m Algorithm: Magi pts/cpuminer-opt-1.7.0 -a scrypt Algorithm: scrypt pts/cpuminer-opt-1.7.0 -a deep Algorithm: Deepcoin pts/cpuminer-opt-1.7.0 -a minotaur Algorithm: Ringcoin pts/cpuminer-opt-1.7.0 -a blake2s Algorithm: Blake-2 S pts/cpuminer-opt-1.7.0 -a allium Algorithm: Garlicoin pts/cpuminer-opt-1.7.0 -a skein Algorithm: Skeincoin pts/cpuminer-opt-1.7.0 -a myr-gr Algorithm: Myriad-Groestl pts/cpuminer-opt-1.7.0 -a lbry Algorithm: LBC, LBRY Credits pts/cpuminer-opt-1.7.0 -a sha256q Algorithm: Quad SHA-256, Pyrite pts/cpuminer-opt-1.7.0 -a sha256t Algorithm: Triple SHA-256, Onecoin pts/build-gcc-1.4.0 Time To Compile pts/svt-av1-2.10.0 --preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 4 - Input: Bosphorus 4K pts/svt-av1-2.10.0 --preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 8 - Input: Bosphorus 4K pts/svt-av1-2.10.0 --preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 12 - Input: Bosphorus 4K pts/svt-av1-2.10.0 --preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 13 - Input: Bosphorus 4K pts/svt-av1-2.10.0 --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-av1-2.10.0 --preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 8 - Input: Bosphorus 1080p pts/svt-av1-2.10.0 --preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 12 - Input: Bosphorus 1080p pts/svt-av1-2.10.0 --preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Preset 13 - Input: Bosphorus 1080p pts/ffmpeg-6.1.0 --encoder=libx264 live Encoder: libx264 - Scenario: Live pts/ffmpeg-6.1.0 --encoder=libx265 live Encoder: libx265 - Scenario: Live pts/ffmpeg-6.1.0 --encoder=libx264 upload Encoder: libx264 - Scenario: Upload pts/ffmpeg-6.1.0 --encoder=libx265 upload Encoder: libx265 - Scenario: Upload pts/ffmpeg-6.1.0 --encoder=libx264 platform Encoder: libx264 - Scenario: Platform pts/ffmpeg-6.1.0 --encoder=libx265 platform Encoder: libx265 - Scenario: Platform pts/ffmpeg-6.1.0 --encoder=libx264 vod Encoder: libx264 - Scenario: Video On Demand pts/ffmpeg-6.1.0 --encoder=libx265 vod Encoder: libx265 - Scenario: Video On Demand pts/vvenc-1.9.1 -i Bosphorus_3840x2160.y4m --preset fast Video Input: Bosphorus 4K - Video Preset: Fast pts/vvenc-1.9.1 -i Bosphorus_3840x2160.y4m --preset faster Video Input: Bosphorus 4K - Video Preset: Faster pts/vvenc-1.9.1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset fast Video Input: Bosphorus 1080p - Video Preset: Fast pts/vvenc-1.9.1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset faster Video Input: Bosphorus 1080p - Video Preset: Faster pts/avifenc-1.4.0 -s 0 Encoder Speed: 0 pts/avifenc-1.4.0 -s 2 Encoder Speed: 2 pts/avifenc-1.4.0 -s 6 Encoder Speed: 6 pts/avifenc-1.4.0 -s 6 -l Encoder Speed: 6, Lossless pts/avifenc-1.4.0 -s 10 -l Encoder Speed: 10, Lossless pts/embree-1.6.0 pathtracer -c crown/crown.ecs Binary: Pathtracer - Model: Crown pts/embree-1.6.0 pathtracer_ispc -c crown/crown.ecs Binary: Pathtracer ISPC - Model: Crown pts/embree-1.6.0 pathtracer -c asian_dragon/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon pts/embree-1.6.0 pathtracer -c asian_dragon_obj/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon Obj pts/embree-1.6.0 pathtracer_ispc -c asian_dragon/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon pts/embree-1.6.0 pathtracer_ispc -c asian_dragon_obj/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon Obj pts/oidn-2.1.0 -r RT.hdr_alb_nrm.3840x2160 -d cpu Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only pts/oidn-2.1.0 -r RT.ldr_alb_nrm.3840x2160 -d cpu Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only pts/oidn-2.1.0 -r RTLightmap.hdr.4096x4096 -d cpu Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only pts/openvkl-2.0.0 vklBenchmarkCPU --benchmark_filter=ispc Benchmark: vklBenchmarkCPU ISPC pts/openvkl-2.0.0 vklBenchmarkCPU --benchmark_filter=scalar Benchmark: vklBenchmarkCPU Scalar pts/ospray-studio-1.2.0 --cameras 1 1 --resolution 3840 2160 --spp 1 --renderer pathtracer Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 2 2 --resolution 3840 2160 --spp 1 --renderer pathtracer Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 3 3 --resolution 3840 2160 --spp 1 --renderer pathtracer Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 1 1 --resolution 3840 2160 --spp 16 --renderer pathtracer Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 1 1 --resolution 3840 2160 --spp 32 --renderer pathtracer Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 2 2 --resolution 3840 2160 --spp 16 --renderer pathtracer Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 2 2 --resolution 3840 2160 --spp 32 --renderer pathtracer Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 3 3 --resolution 3840 2160 --spp 16 --renderer pathtracer Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 3 3 --resolution 3840 2160 --spp 32 --renderer pathtracer Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 1 1 --resolution 1920 1080 --spp 1 --renderer pathtracer Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 2 2 --resolution 1920 1080 --spp 1 --renderer pathtracer Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 3 3 --resolution 1920 1080 --spp 1 --renderer pathtracer Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 1 1 --resolution 1920 1080 --spp 16 --renderer pathtracer Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 1 1 --resolution 1920 1080 --spp 32 --renderer pathtracer Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 2 2 --resolution 1920 1080 --spp 16 --renderer pathtracer Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 2 2 --resolution 1920 1080 --spp 32 --renderer pathtracer Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 3 3 --resolution 1920 1080 --spp 16 --renderer pathtracer Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU pts/ospray-studio-1.2.0 --cameras 3 3 --resolution 1920 1080 --spp 32 --renderer pathtracer Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU pts/build-gem5-1.1.0 Time To Compile pts/blosc-1.3.0 blosclz shuffle 8388608 Test: blosclz shuffle - Buffer Size: 8MB pts/blosc-1.3.0 blosclz shuffle 16777216 Test: blosclz shuffle - Buffer Size: 16MB pts/blosc-1.3.0 blosclz shuffle 33554432 Test: blosclz shuffle - Buffer Size: 32MB pts/blosc-1.3.0 blosclz shuffle 67108864 Test: blosclz shuffle - Buffer Size: 64MB pts/blosc-1.3.0 blosclz noshuffle 8388608 Test: blosclz noshuffle - Buffer Size: 8MB pts/blosc-1.3.0 blosclz shuffle 134217728 Test: blosclz shuffle - Buffer Size: 128MB pts/blosc-1.3.0 blosclz shuffle 268435456 Test: blosclz shuffle - Buffer Size: 256MB pts/blosc-1.3.0 blosclz bitshuffle 8388608 Test: blosclz bitshuffle - Buffer Size: 8MB pts/blosc-1.3.0 blosclz noshuffle 16777216 Test: blosclz noshuffle - Buffer Size: 16MB pts/blosc-1.3.0 blosclz noshuffle 33554432 Test: blosclz noshuffle - Buffer Size: 32MB pts/blosc-1.3.0 blosclz noshuffle 67108864 Test: blosclz noshuffle - Buffer Size: 64MB pts/blosc-1.3.0 blosclz bitshuffle 16777216 Test: blosclz bitshuffle - Buffer Size: 16MB pts/blosc-1.3.0 blosclz bitshuffle 33554432 Test: blosclz bitshuffle - Buffer Size: 32MB pts/blosc-1.3.0 blosclz bitshuffle 67108864 Test: blosclz bitshuffle - Buffer Size: 64MB pts/blosc-1.3.0 blosclz noshuffle 134217728 Test: blosclz noshuffle - Buffer Size: 128MB pts/blosc-1.3.0 blosclz noshuffle 268435456 Test: blosclz noshuffle - Buffer Size: 256MB pts/blosc-1.3.0 blosclz bitshuffle 134217728 Test: blosclz bitshuffle - Buffer Size: 128MB pts/blosc-1.3.0 blosclz bitshuffle 268435456 Test: blosclz bitshuffle - Buffer Size: 256MB pts/cassandra-1.2.0 WRITE Test: Writes