Core i9 13900K Linux Distros

Intel Core i9-13900K testing with a ASUS PRIME Z790-P WIFI (0602 BIOS) and AMD Radeon RX 6800 XT 16GB on Clear Linux OS 37600 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 2211066-NE-DISTROS7610
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AV1 2 Tests
C++ Boost Tests 4 Tests
Timed Code Compilation 4 Tests
C/C++ Compiler Tests 8 Tests
CPU Massive 23 Tests
Creator Workloads 19 Tests
Cryptocurrency Benchmarks, CPU Mining Tests 3 Tests
Cryptography 4 Tests
Database Test Suite 4 Tests
Desktop Graphics 2 Tests
Encoding 6 Tests
Finance 2 Tests
Fortran Tests 4 Tests
Game Development 3 Tests
HPC - High Performance Computing 17 Tests
Imaging 4 Tests
Java 3 Tests
Common Kernel Benchmarks 4 Tests
Machine Learning 6 Tests
Molecular Dynamics 4 Tests
MPI Benchmarks 3 Tests
Multi-Core 25 Tests
Node.js + NPM Tests 3 Tests
NVIDIA GPU Compute 6 Tests
Intel oneAPI 5 Tests
OpenMPI Tests 8 Tests
Programmer / Developer System Benchmarks 8 Tests
Python 3 Tests
Renderers 5 Tests
Scientific Computing 4 Tests
Software Defined Radio 2 Tests
Server 9 Tests
Server CPU Tests 19 Tests
Single-Threaded 6 Tests
Video Encoding 5 Tests
Common Workstation Benchmarks 2 Tests

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Ubuntu 22.10
November 02 2022
  1 Day, 1 Hour, 49 Minutes
Clear Linux
November 05 2022
  14 Hours, 3 Minutes
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  19 Hours, 56 Minutes
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Core i9 13900K Linux Distros Suite 1.0.0 System Test suite extracted from Core i9 13900K Linux Distros. pts/nwchem-1.1.1 Input: C240 Buckyball pts/blender-3.3.1 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Barbershop - Compute: CPU-Only pts/openvkl-1.1.0 vklBenchmark --benchmark_filter=ispc Benchmark: vklBenchmark ISPC pts/build-linux-kernel-1.14.0 allmodconfig Build: allmodconfig pts/tensorflow-2.0.0 --device cpu --batch_size=256 --model=resnet50 Device: CPU - Batch Size: 256 - Model: ResNet-50 pts/memtier-benchmark-1.4.1 -P redis -c 50 --ratio=1:1 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1 pts/onnx-1.5.0 resnet100/resnet100.onnx -e cpu Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard pts/onnx-1.5.0 GPT2/model.onnx -e cpu Model: GPT-2 - Device: CPU - Executor: Standard pts/tensorflow-2.0.0 --device cpu --batch_size=512 --model=googlenet Device: CPU - Batch Size: 512 - Model: GoogLeNet pts/hpcg-1.2.1 pts/minibude-1.0.0 --deck ../data/bm2 --iterations 10 Implementation: OpenMP - Input Deck: BM2 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-1.5.0 sample-4.png out.jxl -q 100 --num_reps 10 Input: PNG - Quality: 100 pts/memtier-benchmark-1.4.1 -P redis -c 50 --ratio=10:1 Protocol: Redis - Clients: 50 - Set To Get Ratio: 10:1 pts/openradioss-1.0.0 Cell_Phone_Drop_0000.rad Cell_Phone_Drop_0001.rad Model: Cell Phone Drop Test pts/memtier-benchmark-1.4.1 -P redis -c 50 --ratio=1:10 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 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/indigobench-1.1.0 --cpuonly --scenes supercar Acceleration: CPU - Scene: Supercar pts/openradioss-1.0.0 BIRD_WINDSHIELD_v1_0000.rad BIRD_WINDSHIELD_v1_0001.rad Model: Bird Strike on Windshield pts/openssl-3.0.1 sha256 Algorithm: SHA256 pts/blender-3.3.1 -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/ffmpeg-3.0.0 --encoder=libx264 upload Encoder: libx264 - Scenario: Upload pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Group By Test Time pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Repartition Test Time pts/spark-1.0.0 -r 1000000 -p 500 Row Count: 1000000 - Partitions: 500 - Inner Join Test Time pts/clickhouse-1.1.0 100M Rows Web Analytics Dataset, Third Run pts/clickhouse-1.1.0 100M Rows Web Analytics Dataset, Second Run pts/clickhouse-1.1.0 100M Rows Web Analytics Dataset, First Run / Cold Cache pts/renaissance-1.3.0 movie-lens Test: ALS Movie Lens 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/hammerdb-mariadb-1.1.0 64 250 Virtual Users: 64 - Warehouses: 250 pts/hammerdb-mariadb-1.1.0 64 100 Virtual Users: 64 - Warehouses: 100 pts/hammerdb-mariadb-1.1.0 32 100 Virtual Users: 32 - Warehouses: 100 pts/hammerdb-mariadb-1.1.0 32 250 Virtual Users: 32 - Warehouses: 250 pts/hammerdb-mariadb-1.1.0 8 100 Virtual Users: 8 - Warehouses: 100 pts/hammerdb-mariadb-1.1.0 16 250 Virtual Users: 16 - Warehouses: 250 pts/hammerdb-mariadb-1.1.0 16 100 Virtual Users: 16 - Warehouses: 100 pts/hammerdb-mariadb-1.1.0 8 250 Virtual Users: 8 - Warehouses: 250 pts/renaissance-1.3.0 future-genetic Test: Genetic Algorithm Using Jenetics + Futures 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/stress-ng-1.6.0 --atomic -1 Test: Atomic pts/stress-ng-1.6.0 --cache -1 Test: CPU Cache pts/rodinia-1.3.2 OMP_HOTSPOT3D Test: OpenMP HotSpot3D 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/blender-3.3.1 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Classroom - Compute: CPU-Only pts/java-gradle-perf-1.1.0 TEST_REACTOR Gradle Build: Reactor pts/renaissance-1.3.0 akka-uct Test: Akka Unbalanced Cobwebbed Tree pts/stress-ng-1.6.0 --futex -1 Test: Futex pts/stress-ng-1.6.0 --sock -1 Test: Socket Activity pts/gromacs-1.7.0 mpi-build water-cut1.0_GMX50_bare/1536 Implementation: MPI CPU - Input: water_GMX50_bare pts/tensorflow-2.0.0 --device cpu --batch_size=256 --model=googlenet Device: CPU - Batch Size: 256 - Model: GoogLeNet pts/polyhedron-1.0.1 fatigue2 Benchmark: fatigue2 pts/build-nodejs-1.2.0 Time To Compile pts/ffmpeg-3.0.0 --encoder=libx265 upload Encoder: libx265 - Scenario: Upload 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/ffmpeg-3.0.0 --encoder=libx265 vod Encoder: libx265 - Scenario: Video On Demand pts/ffmpeg-3.0.0 --encoder=libx265 platform Encoder: libx265 - Scenario: Platform pts/onnx-1.5.0 fcn-resnet101-11/model.onnx -e cpu Model: fcn-resnet101-11 - Device: CPU - Executor: Standard pts/polyhedron-1.0.1 tfft2 Benchmark: tfft2 pts/onnx-1.5.0 bertsquad-12/bertsquad-12.onnx -e cpu Model: bertsquad-12 - Device: CPU - Executor: Standard pts/onnx-1.5.0 yolov4/yolov4.onnx -e cpu Model: yolov4 - Device: CPU - Executor: Standard pts/onnx-1.5.0 super_resolution/super_resolution.onnx -e cpu Model: super-resolution-10 - Device: CPU - Executor: Standard pts/financebench-1.1.1 Bonds/OpenMP/bondsEngine.exe Benchmark: Bonds OpenMP pts/renaissance-1.3.0 page-rank Test: Apache Spark PageRank pts/openradioss-1.0.0 Bumper_Beam_AP_meshed_0000.rad Bumper_Beam_AP_meshed_0001.rad Model: Bumper Beam 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/ffmpeg-3.0.0 --encoder=libx264 vod Encoder: libx264 - Scenario: Video On Demand pts/openradioss-1.0.0 RUBBER_SEAL_IMPDISP_GEOM_0000.rad RUBBER_SEAL_IMPDISP_GEOM_0001.rad Model: Rubber O-Ring Seal Installation pts/ffmpeg-3.0.0 --encoder=libx264 platform Encoder: libx264 - Scenario: Platform pts/appleseed-1.0.1 emily.appleseed Scene: Emily 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/tensorflow-2.0.0 --device cpu --batch_size=512 --model=alexnet Device: CPU - Batch Size: 512 - Model: AlexNet pts/xmrig-1.1.0 --bench=1M Variant: Monero - Hash Count: 1M pts/polyhedron-1.0.1 gas_dyn2 Benchmark: gas_dyn2 pts/svt-hevc-1.2.1 -encMode 1 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: 1 - Input: Bosphorus 4K pts/renaissance-1.3.0 dotty Test: Scala Dotty pts/pyperformance-1.0.2 python_startup Benchmark: python_startup 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/npb-1.4.5 sp.C Test / Class: SP.C pts/tensorflow-2.0.0 --device cpu --batch_size=64 --model=resnet50 Device: CPU - Batch Size: 64 - Model: ResNet-50 pts/nginx-3.0.0 -c 1000 Connections: 1000 pts/nginx-3.0.0 -c 500 Connections: 500 pts/nginx-3.0.0 -c 200 Connections: 200 pts/nginx-3.0.0 -c 100 Connections: 100 pts/cpuminer-opt-1.6.0 -a blake2s Algorithm: Blake-2 S pts/stress-ng-1.6.0 --mutex -1 Test: Mutex pts/stress-ng-1.6.0 --crypt -1 Test: Crypto pts/financebench-1.1.1 Repo/OpenMP/repoEngine.exe Benchmark: Repo OpenMP pts/rodinia-1.3.2 OMP_LAVAMD Test: OpenMP LavaMD 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 sample-4.png out.jxl -q 80 --num_reps 50 Input: PNG - Quality: 80 pts/warsow-1.6.0 +vid_width 1920 +vid_height 1080 Resolution: 1920 x 1080 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/warsow-1.6.0 +vid_width 3840 +vid_height 2160 Resolution: 3840 x 2160 pts/cpuminer-opt-1.6.0 -a skein Algorithm: Skeincoin 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/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario async Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream 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/blender-3.3.1 -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/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/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/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/v-ray-1.4.0 -m vray Mode: CPU 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 90 --num_reps 40 Input: PNG - Quality: 90 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/face-detection-0206/FP16/face-detection-0206.xml -d CPU Model: Face Detection FP16 - Device: CPU pts/xonotic-1.6.0 +vid_width 3840 +vid_height 2160 +exec effects-ultimate.cfg Resolution: 3840 x 2160 - Effects Quality: Ultimate pts/renaissance-1.3.0 als Test: Apache Spark ALS pts/indigobench-1.1.0 --cpuonly --scenes bedroom Acceleration: CPU - Scene: Bedroom pts/xonotic-1.6.0 +vid_width 1920 +vid_height 1080 +exec effects-ultimate.cfg Resolution: 1920 x 1080 - Effects Quality: Ultimate pts/renaissance-1.3.0 finagle-http Test: Finagle HTTP Requests pts/appleseed-1.0.1 material_tester_ambient_occlusion.appleseed Scene: Material Tester pts/xmrig-1.1.0 -a rx/wow --bench=1M Variant: Wownero - Hash Count: 1M 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/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/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/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/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/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection 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/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/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/stress-ng-1.6.0 --vecmath -1 Test: Vector Math pts/openssl-3.0.1 rsa4096 Algorithm: RSA4096 pts/npb-1.4.5 bt.C Test / Class: BT.C pts/build-python-1.0.0 --enable-optimizations --with-lto Build Configuration: Released Build, PGO + LTO Optimized pts/npb-1.4.5 ft.C Test / Class: FT.C pts/appleseed-1.0.1 disney_material_1.appleseed Scene: Disney Material pts/compress-7zip-1.10.0 Test: Decompression Rating pts/compress-7zip-1.10.0 Test: Compression Rating pts/tensorflow-2.0.0 --device cpu --batch_size=256 --model=alexnet Device: CPU - Batch Size: 256 - Model: AlexNet pts/svt-av1-2.6.0 --preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 4 - Input: Bosphorus 4K pts/oidn-1.4.0 -r RT.ldr_alb_nrm.3840x2160 Run: RT.ldr_alb_nrm.3840x2160 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/renaissance-1.3.0 reactors Test: Savina Reactors.IO pts/blender-3.3.1 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: BMW27 - Compute: CPU-Only pts/xonotic-1.6.0 +vid_width 3840 +vid_height 2160 +exec effects-ultra.cfg Resolution: 3840 x 2160 - Effects Quality: Ultra pts/xonotic-1.6.0 +vid_width 1920 +vid_height 1080 +exec effects-ultra.cfg Resolution: 1920 x 1080 - Effects Quality: Ultra pts/rodinia-1.3.2 OMP_LEUKOCYTE Test: OpenMP Leukocyte pts/polyhedron-1.0.1 channel2 Benchmark: channel2 pts/minibude-1.0.0 --deck ../data/bm1 --iterations 500 Implementation: OpenMP - Input Deck: BM1 pts/tensorflow-2.0.0 --device cpu --batch_size=32 --model=resnet50 Device: CPU - Batch Size: 32 - Model: ResNet-50 pts/npb-1.4.5 ep.D Test / Class: EP.D 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/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/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario sync Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream pts/stress-ng-1.6.0 --cpu -1 --cpu-method all Test: CPU Stress 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/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario async Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream pts/node-web-tooling-1.0.1 pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms system/compress-zstd-1.5.0 -b19 Compression Level: 19 - Decompression Speed system/compress-zstd-1.5.0 -b19 Compression Level: 19 - Compression Speed pts/polyhedron-1.0.1 mp_prop_design Benchmark: mp_prop_design pts/build-linux-kernel-1.14.0 defconfig Build: defconfig pts/npb-1.4.5 is.D Test / Class: IS.D 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: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/stargate-1.0.1 96000 512 Sample Rate: 96000 - Buffer Size: 512 pts/stargate-1.0.1 96000 1024 Sample Rate: 96000 - Buffer Size: 1024 pts/npb-1.4.5 lu.C Test / Class: LU.C pts/ffmpeg-3.0.0 --encoder=libx265 live Encoder: libx265 - Scenario: Live 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 system/compress-zstd-1.5.0 -b19 --long Compression Level: 19, Long Mode - Decompression Speed system/compress-zstd-1.5.0 -b19 --long Compression Level: 19, Long Mode - Compression Speed 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/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 sync Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream 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/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time pts/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time pts/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Inner Join Test Time pts/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Repartition Test Time pts/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Group By Test Time pts/spark-1.0.0 -r 1000000 -p 100 Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark pts/chia-vdf-1.1.0 square Test: Square Plain C++ pts/stress-ng-1.6.0 --memcpy -1 Test: Memory Copying pts/chia-vdf-1.1.0 square_asm Test: Square Assembly Optimized pts/tensorflow-2.0.0 --device cpu --batch_size=64 --model=googlenet Device: CPU - Batch Size: 64 - Model: GoogLeNet system/rawtherapee-1.0.1 Total Benchmark Time pts/pyperformance-1.0.2 django_template Benchmark: django_template pts/tesseract-1.1.0 -w1920 -h1080 Resolution: 1920 x 1080 pts/pyhpc-3.0.0 --device cpu -b numpy -s 16384 benchmarks/isoneutral_mixing/ Device: CPU - Backend: Numpy - Project Size: 16384 - Benchmark: Isoneutral Mixing pts/tesseract-1.1.0 -w3840 -h2160 Resolution: 3840 x 2160 pts/sqlite-speedtest-1.0.1 Timed Time - Size 1,000 pts/stress-ng-1.6.0 --rdrand -1 Test: x86_64 RdRand pts/polyhedron-1.0.1 test_fpu2 Benchmark: test_fpu2 pts/stress-ng-1.6.0 --msg -1 Test: System V Message Passing pts/cpuminer-opt-1.6.0 -a x25x Algorithm: x25x pts/cpuminer-opt-1.6.0 -a allium Algorithm: Garlicoin pts/stress-ng-1.6.0 --fork -1 Test: Forking pts/cpuminer-opt-1.6.0 -a scrypt Algorithm: scrypt pts/stress-ng-1.6.0 --mmap -1 Test: MMAP pts/stress-ng-1.6.0 --qsort -1 Test: Glibc Qsort Data Sorting pts/stress-ng-1.6.0 --io-uring -1 Test: IO_uring pts/stress-ng-1.6.0 --numa -1 Test: NUMA pts/stress-ng-1.6.0 --malloc -1 Test: Malloc pts/stress-ng-1.6.0 --sendfile -1 Test: SENDFILE pts/stress-ng-1.6.0 --memfd -1 Test: MEMFD pts/stress-ng-1.6.0 --matrix -1 Test: Matrix Math pts/stress-ng-1.6.0 --sem -1 Test: Semaphores 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/cpuminer-opt-1.6.0 -a deep Algorithm: Deepcoin pts/cpuminer-opt-1.6.0 -a m7m Algorithm: Magi 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/cpuminer-opt-1.6.0 -a minotaur Algorithm: Ringcoin pts/pyperformance-1.0.2 raytrace Benchmark: raytrace pts/stargate-1.0.1 44100 512 Sample Rate: 44100 - Buffer Size: 512 pts/build-wasmer-1.2.0 Time To Compile 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/stargate-1.0.1 44100 1024 Sample Rate: 44100 - Buffer Size: 1024 pts/pyperformance-1.0.2 float Benchmark: float pts/pyperformance-1.0.2 chaos Benchmark: chaos pts/pyperformance-1.0.2 regex_compile Benchmark: regex_compile pts/ffmpeg-3.0.0 --encoder=libx264 live Encoder: libx264 - Scenario: Live pts/pyperformance-1.0.2 pickle_pure_python Benchmark: pickle_pure_python pts/pyperformance-1.0.2 2to3 Benchmark: 2to3 pts/webp-1.2.0 -q 100 -lossless -m 6 Encode Settings: Quality 100, Lossless, Highest Compression pts/pyperformance-1.0.2 nbody Benchmark: nbody pts/dacapobench-1.0.1 h2 Java Test: H2 pts/pyperformance-1.0.2 pathlib Benchmark: pathlib pts/pyperformance-1.0.2 go Benchmark: go pts/rodinia-1.3.2 OMP_CFD Test: OpenMP CFD Solver 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/tensorflow-2.0.0 --device cpu --batch_size=16 --model=resnet50 Device: CPU - Batch Size: 16 - Model: ResNet-50 pts/rodinia-1.3.2 OMP_STREAMCLUSTER Test: OpenMP Streamcluster pts/srsran-1.2.0 lib/src/phy/dft/test/ofdm_test -N 2048 -n 100 -r 500000 Test: OFDM_Test pts/polyhedron-1.0.1 induct2 Benchmark: induct2 pts/renaissance-1.3.0 naive-bayes Test: Apache Spark Bayes pts/encodec-1.0.1 -b 24 Target Bandwidth: 24 kbps pts/pyperformance-1.0.2 crypto_pyaes Benchmark: crypto_pyaes pts/spacy-1.0.0 Model: en_core_web_lg pts/spacy-1.0.0 Model: en_core_web_trf pts/pyperformance-1.0.2 json_loads Benchmark: json_loads pts/liquid-dsp-1.0.0 -n 8 -b 256 -f 57 Threads: 8 - Buffer Length: 256 - Filter Length: 57 pts/renaissance-1.3.0 dec-tree Test: Random Forest pts/encodec-1.0.1 -b 6 Target Bandwidth: 6 kbps pts/encodec-1.0.1 -b 3 Target Bandwidth: 3 kbps pts/encodec-1.0.1 -b 1.5 Target Bandwidth: 1.5 kbps pts/svt-vp9-1.3.1 -tune 2 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: VMAF Optimized - Input: Bosphorus 4K pts/renaissance-1.3.0 db-shootout Test: In-Memory Database Shootout pts/npb-1.4.5 cg.C Test / Class: CG.C pts/svt-hevc-1.2.1 -encMode 10 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: 10 - Input: Bosphorus 4K pts/tensorflow-2.0.0 --device cpu --batch_size=32 --model=googlenet Device: CPU - Batch Size: 32 - Model: GoogLeNet pts/npb-1.4.5 sp.B Test / Class: SP.B pts/polyhedron-1.0.1 rnflow Benchmark: rnflow pts/unvanquished-1.7.0 +set r_customWidth 3840 +set r_customHeight 2160 +preset presets/graphics/ultra.cfg Resolution: 3840 x 2160 - Effects Quality: Ultra pts/polyhedron-1.0.1 doduc Benchmark: doduc pts/unvanquished-1.7.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/ultra.cfg Resolution: 1920 x 1080 - Effects Quality: Ultra pts/unvanquished-1.7.0 +set r_customWidth 3840 +set r_customHeight 2160 +preset presets/graphics/high.cfg Resolution: 3840 x 2160 - Effects Quality: High pts/tensorflow-2.0.0 --device cpu --batch_size=64 --model=alexnet Device: CPU - Batch Size: 64 - Model: AlexNet pts/unvanquished-1.7.0 +set r_customWidth 1920 +set r_customHeight 1080 +preset presets/graphics/high.cfg Resolution: 1920 x 1080 - Effects Quality: High pts/libraw-1.0.0 Post-Processing Benchmark pts/quantlib-1.0.0 pts/polyhedron-1.0.1 capacita Benchmark: capacita pts/aom-av1-3.5.0 --cpu-used=6 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K pts/cloudsuite-ga-1.0.1 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/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/polyhedron-1.0.1 protein Benchmark: protein pts/webp-1.2.0 -q 100 -lossless Encode Settings: Quality 100, Lossless pts/polyhedron-1.0.1 ac Benchmark: ac pts/pybench-1.1.3 Total For Average Test Times 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/polyhedron-1.0.1 air Benchmark: air pts/aom-av1-3.5.0 --cpu-used=8 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K pts/phpbench-1.1.6 PHP Benchmark Suite 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/tensorflow-2.0.0 --device cpu --batch_size=32 --model=alexnet Device: CPU - Batch Size: 32 - Model: AlexNet pts/node-express-loadtest-1.0.1 pts/pyhpc-3.0.0 --device cpu -b numpy -s 16384 benchmarks/equation_of_state/ Device: CPU - Backend: Numpy - Project Size: 16384 - Benchmark: Equation of State pts/svt-av1-2.6.0 --preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 8 - Input: Bosphorus 4K pts/tensorflow-2.0.0 --device cpu --batch_size=16 --model=googlenet Device: CPU - Batch Size: 16 - Model: GoogLeNet pts/aom-av1-3.5.0 --cpu-used=9 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K pts/dacapobench-1.0.1 tradesoap Java Test: Tradesoap pts/aom-av1-3.5.0 --cpu-used=10 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K pts/npb-1.4.5 mg.C Test / Class: MG.C pts/polyhedron-1.0.1 aermod Benchmark: aermod pts/cloudsuite-ma-1.0.1 pts/svt-hevc-1.2.1 -encMode 7 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: 7 - Input: Bosphorus 4K pts/polyhedron-1.0.1 mdbx Benchmark: mdbx 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/tensorflow-2.0.0 --device cpu --batch_size=16 --model=alexnet Device: CPU - Batch Size: 16 - Model: AlexNet pts/svt-vp9-1.3.1 -tune 0 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: Visual Quality Optimized - Input: Bosphorus 4K pts/graph500-1.0.1 26 Scale: 26 pts/webp-1.2.0 -q 100 -m 6 Encode Settings: Quality 100, Highest Compression pts/svt-vp9-1.3.1 -tune 1 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 4K pts/svt-av1-2.6.0 --preset 10 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 10 - Input: Bosphorus 4K pts/polyhedron-1.0.1 linpk Benchmark: linpk pts/tensorflow-2.0.0 --device cpu --batch_size=512 --model=resnet50 Device: CPU - Batch Size: 512 - Model: ResNet-50 pts/build-python-1.0.0 Build Configuration: Default pts/dacapobench-1.0.1 tradebeans Java Test: Tradebeans pts/dacapobench-1.0.1 jython Java Test: Jython pts/svt-av1-2.6.0 --preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 12 - Input: Bosphorus 4K 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/npb-1.4.5 ep.C Test / Class: EP.C pts/webp-1.2.0 -q 100 Encode Settings: Quality 100 pts/webp-1.2.0 Encode Settings: Default pts/dacapobench-1.0.1 eclipse Java Test: Eclipse pts/ctx-clock-1.0.0 Context Switch Time pts/pyhpc-3.0.0 --device cpu -b tensorflow -s 16384 benchmarks/equation_of_state/ Device: CPU - Backend: TensorFlow - Project Size: 16384 - Benchmark: Equation of State pts/pyhpc-3.0.0 --device cpu -b pytorch -s 16384 benchmarks/equation_of_state/ Device: CPU - Backend: PyTorch - Project Size: 16384 - Benchmark: Equation of State pts/pyhpc-3.0.0 --device cpu -b aesara -s 16384 benchmarks/equation_of_state/ Device: CPU - Backend: Aesara - Project Size: 16384 - Benchmark: Equation of State pts/pyhpc-3.0.0 --device cpu -b numba -s 16384 benchmarks/isoneutral_mixing/ Device: CPU - Backend: Numba - Project Size: 16384 - Benchmark: Isoneutral Mixing pts/pyhpc-3.0.0 --device cpu -b jax -s 16384 benchmarks/isoneutral_mixing/ Device: CPU - Backend: JAX - Project Size: 16384 - Benchmark: Isoneutral Mixing pts/pyhpc-3.0.0 --device cpu -b tensorflow -s 16384 benchmarks/isoneutral_mixing/ Device: CPU - Backend: TensorFlow - Project Size: 16384 - Benchmark: Isoneutral Mixing pts/pyhpc-3.0.0 --device cpu -b aesara -s 16384 benchmarks/isoneutral_mixing/ Device: CPU - Backend: Aesara - Project Size: 16384 - Benchmark: Isoneutral Mixing pts/pyhpc-3.0.0 --device cpu -b pytorch -s 16384 benchmarks/isoneutral_mixing/ Device: CPU - Backend: PyTorch - Project Size: 16384 - Benchmark: Isoneutral Mixing pts/pyhpc-3.0.0 --device cpu -b jax -s 16384 benchmarks/equation_of_state/ Device: CPU - Backend: JAX - Project Size: 16384 - Benchmark: Equation of State pts/pyhpc-3.0.0 --device cpu -b numba -s 16384 benchmarks/equation_of_state/ Device: CPU - Backend: Numba - Project Size: 16384 - Benchmark: Equation of State pts/node-octane-1.0.1 pts/nginx-3.0.0 -c 20 Connections: 20 pts/nginx-3.0.0 -c 1 Connections: 1