New Tests

2 x Intel Xeon Platinum 8380 testing with a Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS) and ASPEED 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 2209031-NE-2209025NE82
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AV1 2 Tests
Timed Code Compilation 3 Tests
C/C++ Compiler Tests 15 Tests
Compression Tests 2 Tests
CPU Massive 23 Tests
Creator Workloads 15 Tests
Database Test Suite 8 Tests
Encoding 6 Tests
Fortran Tests 2 Tests
Game Development 2 Tests
Go Language Tests 3 Tests
HPC - High Performance Computing 10 Tests
Imaging 3 Tests
Java 2 Tests
Common Kernel Benchmarks 3 Tests
Machine Learning 6 Tests
Molecular Dynamics 3 Tests
MPI Benchmarks 3 Tests
Multi-Core 23 Tests
Node.js + NPM Tests 2 Tests
NVIDIA GPU Compute 2 Tests
Intel oneAPI 4 Tests
OpenMPI Tests 3 Tests
Programmer / Developer System Benchmarks 6 Tests
Python Tests 4 Tests
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Scientific Computing 3 Tests
Server 13 Tests
Server CPU Tests 15 Tests
Single-Threaded 3 Tests
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CentOS Stream 9
August 31 2022
  23 Hours, 41 Minutes
Clear Linux 36990
September 01 2022
  19 Hours, 13 Minutes
Ubuntu 20.04.1 LTS
September 02 2022
  21 Hours, 41 Minutes
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  21 Hours, 32 Minutes

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New Tests Suite 1.0.0 System Test suite extracted from New Tests. pts/pgbench-1.11.1 -s 100 -c 500 -S Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency pts/pgbench-1.11.1 -s 100 -c 500 -S Scaling Factor: 100 - Clients: 500 - Mode: Read Only pts/tnn-1.1.0 -dt NAIVE -mp ../benchmark/benchmark-model/densenet.tnnproto Target: CPU - Model: DenseNet pts/renaissance-1.3.0 reactors Test: Savina Reactors.IO pts/stockfish-1.4.0 Total Time pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - Calculate Pi Benchmark pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - SHA-512 Benchmark Time pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - Broadcast Inner Join Test Time pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - Inner Join Test Time pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - Repartition Test Time pts/spark-1.0.0 -r 40000000 -p 500 Row Count: 40000000 - Partitions: 500 - Group By Test Time pts/pgbench-1.11.1 -s 100 -c 250 -S Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency pts/pgbench-1.11.1 -s 100 -c 250 -S Scaling Factor: 100 - Clients: 250 - Mode: Read Only pts/onnx-1.5.0 GPT2/model.onnx -e cpu Model: GPT-2 - Device: CPU - Executor: Standard pts/onnx-1.5.0 resnet100/resnet100.onnx -e cpu Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/onnx-1.5.0 fcn-resnet101-11/model.onnx -e cpu Model: fcn-resnet101-11 - Device: CPU - Executor: Standard pts/renaissance-1.3.0 finagle-http Test: Finagle HTTP Requests pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/ospray-2.10.0 --benchmark_filter=particle_volume/scivis/real_time Benchmark: particle_volume/scivis/real_time pts/renaissance-1.3.0 movie-lens Test: ALS Movie Lens pts/tensorflow-lite-1.1.0 --graph=inception_v4.tflite Model: Inception V4 pts/memtier-benchmark-1.4.0 -P redis -c 50 --ratio=5:1 Protocol: Redis - Clients: 50 - Set To Get Ratio: 5:1 pts/ospray-2.10.0 --benchmark_filter=particle_volume/pathtracer/real_time Benchmark: particle_volume/pathtracer/real_time 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/mnn-2.1.0 Model: inception-v3 pts/mnn-2.1.0 Model: mobilenet-v1-1.0 pts/mnn-2.1.0 Model: MobileNetV2_224 pts/mnn-2.1.0 Model: SqueezeNetV1.0 pts/mnn-2.1.0 Model: resnet-v2-50 pts/mnn-2.1.0 Model: squeezenetv1.1 pts/mnn-2.1.0 Model: mobilenetV3 pts/mnn-2.1.0 Model: nasnet pts/tensorflow-lite-1.1.0 --graph=nasnet_mobile.tflite Model: NASNet Mobile pts/tensorflow-lite-1.1.0 --graph=squeezenet.tflite Model: SqueezeNet pts/blender-3.2.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Barbershop - Compute: CPU-Only pts/onnx-1.5.0 yolov4/yolov4.onnx -e cpu Model: yolov4 - Device: CPU - Executor: Standard pts/ospray-2.10.0 --benchmark_filter=particle_volume/ao/real_time Benchmark: particle_volume/ao/real_time pts/lammps-1.4.0 benchmark_20k_atoms.in Model: 20k Atoms pts/onnx-1.5.0 super_resolution/super_resolution.onnx -e cpu Model: super-resolution-10 - Device: CPU - Executor: Standard pts/tensorflow-lite-1.1.0 --graph=inception_resnet_v2.tflite Model: Inception ResNet V2 pts/apache-2.0.1 -c 1000 Concurrent Requests: 1000 pts/renaissance-1.3.0 db-shootout Test: In-Memory Database Shootout pts/blosc-1.2.0 blosclz shuffle Test: blosclz shuffle pts/memtier-benchmark-1.4.0 -P redis -c 50 --ratio=1:10 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 pts/tensorflow-lite-1.1.0 --graph=mobilenet_v1_1.0_224.tflite Model: Mobilenet Float 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/graphics-magick-2.1.0 -colorspace HWB Operation: HWB Color Space pts/blosc-1.2.0 blosclz bitshuffle Test: blosclz bitshuffle pts/hpcg-1.2.1 pts/build-llvm-1.4.0 Ninja Build System: Ninja pts/vpxenc-3.1.0 --cpu-used=0 ~/Bosphorus_3840x2160.y4m --width=3840 --height=2160 Speed: Speed 0 - Input: Bosphorus 4K 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/tensorflow-lite-1.1.0 --graph=mobilenet_v1_1.0_224_quant.tflite Model: Mobilenet Quant 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/stress-ng-1.5.1 --atomic 0 Test: Atomic 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/stress-ng-1.5.1 --futex 0 Test: Futex pts/graphics-magick-2.1.0 -resize 50% Operation: Resizing pts/ospray-2.10.0 --benchmark_filter=gravity_spheres_volume/dim_512/scivis/real_time Benchmark: gravity_spheres_volume/dim_512/scivis/real_time pts/ospray-2.10.0 --benchmark_filter=gravity_spheres_volume/dim_512/ao/real_time Benchmark: gravity_spheres_volume/dim_512/ao/real_time pts/pgbench-1.11.1 -s 100 -c 250 Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency pts/pgbench-1.11.1 -s 100 -c 250 Scaling Factor: 100 - Clients: 250 - Mode: Read Write pts/pgbench-1.11.1 -s 100 -c 500 Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency pts/pgbench-1.11.1 -s 100 -c 500 Scaling Factor: 100 - Clients: 500 - Mode: Read Write pts/graphics-magick-2.1.0 -rotate 90 Operation: Rotate 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 1 1 --resolution 3840 2160 --spp 32 --renderer pathtracer Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer pts/ospray-2.10.0 --benchmark_filter=gravity_spheres_volume/dim_512/pathtracer/real_time Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time pts/onnx-1.5.0 fcn-resnet101-11/model.onnx -e cpu -P Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 GPT2/model.onnx -e cpu -P Model: GPT-2 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 resnet100/resnet100.onnx -e cpu -P Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 bertsquad-12/bertsquad-12.onnx -e cpu -P Model: bertsquad-12 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 yolov4/yolov4.onnx -e cpu -P Model: yolov4 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 bertsquad-12/bertsquad-12.onnx -e cpu Model: bertsquad-12 - Device: CPU - Executor: Standard pts/natron-1.1.0 Natron_2.3.12_Spaceship/Natron_project/Spaceship_Natron.ntp Input: Spaceship system/compress-zstd-1.5.0 -b8 Compression Level: 8 - Decompression Speed system/compress-zstd-1.5.0 -b8 Compression Level: 8 - Compression Speed pts/onnx-1.5.0 super_resolution/super_resolution.onnx -e cpu -P Model: super-resolution-10 - Device: CPU - Executor: Parallel pts/graphics-magick-2.1.0 -operator all Noise-Gaussian 30% Operation: Noise-Gaussian pts/renaissance-1.3.0 naive-bayes Test: Apache Spark Bayes 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/redis-1.4.0 -t set -c 500 Test: SET - Parallel Connections: 500 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/stress-ng-1.5.1 --sock 0 Test: Socket Activity 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/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/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/influxdb-1.0.1 -c 4 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/nginx-2.0.1 -c 1000 Concurrent Requests: 1000 pts/build-linux-kernel-1.14.0 defconfig Build: defconfig system/compress-zstd-1.5.0 -b3 Compression Level: 3 - Decompression Speed system/compress-zstd-1.5.0 -b3 Compression Level: 3 - Compression Speed pts/blender-3.2.0 -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/avifenc-1.2.0 -s 0 Encoder Speed: 0 system/compress-zstd-1.5.0 -b3 --long Compression Level: 3, Long Mode - Compression Speed pts/redis-1.4.0 -t get -c 500 Test: GET - Parallel Connections: 500 pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/node-web-tooling-1.0.1 pts/redis-1.4.0 -t set -c 1000 Test: SET - Parallel Connections: 1000 pts/tnn-1.1.0 -dt NAIVE -mp ../benchmark/benchmark-model/mobilenet_v2.tnnproto Target: CPU - Model: MobileNet v2 pts/stress-ng-1.5.1 --msg 0 Test: System V Message Passing 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/FP32/person-detection-0106.xml -d CPU Model: Person Detection FP32 - 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/keydb-1.3.1 pts/memtier-benchmark-1.4.0 -P redis -c 100 --ratio=5:1 Protocol: Redis - Clients: 100 - Set To Get Ratio: 5:1 pts/memtier-benchmark-1.4.0 -P redis -c 100 --ratio=1:10 Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 pts/simdjson-2.0.1 partial_tweets Throughput Test: PartialTweets pts/stress-ng-1.5.1 --switch 0 Test: Context Switching pts/simdjson-2.0.1 distinct_user_id Throughput Test: DistinctUserID pts/simdjson-2.0.1 top_tweet Throughput Test: TopTweet 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/dragonflydb-1.0.0 -c 50 --ratio=5:1 Clients: 50 - Set To Get Ratio: 5:1 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=1:1 Clients: 50 - Set To Get Ratio: 1:1 pts/blender-3.2.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Classroom - Compute: CPU-Only 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/renaissance-1.3.0 dec-tree Test: Random Forest 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/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/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-INT8/weld-porosity-detection-0001.xml -d CPU Model: Weld Porosity Detection FP16-INT8 - Device: CPU pts/stress-ng-1.5.1 --cache 0 Test: CPU Cache pts/node-express-loadtest-1.0.1 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 -swirl 90 Operation: Swirl pts/build-gdb-1.1.0 Time To Compile pts/simdjson-2.0.1 kostya Throughput Test: Kostya 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/onednn-1.8.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU pts/simdjson-2.0.1 large_random Throughput Test: LargeRandom pts/compress-7zip-1.10.0 Test: Decompression Rating pts/compress-7zip-1.10.0 Test: Compression Rating pts/stress-ng-1.5.1 --str 0 Test: Glibc C String Functions pts/avifenc-1.2.0 -s 2 Encoder Speed: 2 pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/webp-1.0.0 -q 100 -lossless -m 6 Encode Settings: Quality 100, Lossless, Highest Compression pts/unpack-linux-1.2.0 linux-5.19.tar.xz system/compress-zstd-1.5.0 -b3 --long Compression Level: 3, Long Mode - Decompression Speed pts/x264-2.7.0 Bosphorus_3840x2160.y4m Video Input: Bosphorus 4K system/compress-zstd-1.5.0 -b8 --long Compression Level: 8, Long Mode - Decompression Speed system/compress-zstd-1.5.0 -b8 --long Compression Level: 8, Long Mode - Compression Speed pts/avifenc-1.2.0 -s 6 -l Encoder Speed: 6, Lossless pts/blender-3.2.0 -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/redis-1.4.0 -t get -c 1000 Test: GET - Parallel Connections: 1000 pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms pts/dacapobench-1.0.1 jython Java Test: Jython pts/stress-ng-1.5.1 --numa 0 Test: NUMA pts/stress-ng-1.5.1 --rdrand 0 Test: x86_64 RdRand pts/stress-ng-1.5.1 --io-uring 0 Test: IO_uring pts/stress-ng-1.5.1 --malloc 0 Test: Malloc pts/stress-ng-1.5.1 --fork 0 Test: Forking pts/stress-ng-1.5.1 --memcpy 0 Test: Memory Copying pts/stress-ng-1.5.1 --mmap 0 Test: MMAP pts/stress-ng-1.5.1 --cpu 0 --cpu-method all Test: CPU Stress pts/stress-ng-1.5.1 --sem 0 Test: Semaphores pts/stress-ng-1.5.1 --sendfile 0 Test: SENDFILE pts/stress-ng-1.5.1 --memfd 0 Test: MEMFD pts/stress-ng-1.5.1 --qsort 0 Test: Glibc Qsort Data Sorting pts/stress-ng-1.5.1 --crypt 0 Test: Crypto pts/stress-ng-1.5.1 --matrix 0 Test: Matrix Math pts/stress-ng-1.5.1 --vecmath 0 Test: Vector Math pts/gromacs-1.7.0 mpi-build water-cut1.0_GMX50_bare/1536 Implementation: MPI CPU - Input: water_GMX50_bare pts/redis-1.4.0 -t set -c 50 Test: SET - Parallel Connections: 50 pts/avifenc-1.2.0 -s 10 -l Encoder Speed: 10, Lossless pts/blender-3.2.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: BMW27 - Compute: CPU-Only pts/tnn-1.1.0 -dt NAIVE -mp ../benchmark/benchmark-model/squeezenet_v1.1.tnnproto Target: CPU - Model: SqueezeNet v1.1 pts/redis-1.4.0 -t get -c 50 Test: GET - Parallel Connections: 50 system/openssl-1.1.2 pts/memtier-benchmark-1.4.0 -P redis -c 500 --ratio=5:1 Protocol: Redis - Clients: 500 - Set To Get Ratio: 5:1 pts/memtier-benchmark-1.4.0 -P redis -c 500 --ratio=1:10 Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10 pts/astcenc-1.4.0 -medium -repeats 20 Preset: Medium pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/webp-1.0.0 -q 100 -m 6 Encode Settings: Quality 100, Highest Compression pts/webp-1.0.0 -q 100 -lossless Encode Settings: Quality 100, Lossless pts/svt-hevc-1.2.1 -encMode 10 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: 10 - Input: Bosphorus 4K pts/dacapobench-1.0.1 h2 Java Test: H2 pts/svt-av1-2.6.0 --preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 8 - Input: Bosphorus 4K pts/astcenc-1.4.0 -exhaustive -repeats 2 Preset: Exhaustive pts/svt-vp9-1.3.1 -tune 0 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: Visual Quality Optimized - Input: Bosphorus 4K pts/avifenc-1.2.0 -s 6 Encoder Speed: 6 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-vp9-1.3.1 -tune 2 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: VMAF Optimized - Input: Bosphorus 4K pts/webp-1.0.0 -q 100 Encode Settings: Quality 100 pts/astcenc-1.4.0 -thorough -repeats 10 Preset: Thorough pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU pts/svt-av1-2.6.0 --preset 10 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 10 - Input: Bosphorus 4K pts/svt-hevc-1.2.1 -encMode 7 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Tuning: 7 - Input: Bosphorus 4K pts/tnn-1.1.0 -dt NAIVE -mp ../benchmark/benchmark-model/shufflenet_v2.tnnproto Target: CPU - Model: SqueezeNet v2 pts/astcenc-1.4.0 -fast -repeats 120 Preset: Fast pts/webp-1.0.0 Encode Settings: Default pts/svt-av1-2.6.0 --preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 12 - Input: Bosphorus 4K 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=5:1 Clients: 200 - Set To Get Ratio: 5:1 pts/dragonflydb-1.0.0 -c 200 --ratio=1:5 Clients: 200 - Set To Get Ratio: 1:5 pts/onednn-1.8.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/lammps-1.4.0 in.rhodo Model: Rhodopsin Protein