Cascade Lake Clear Linux 2021

2 x Intel Xeon Platinum 8280 testing with a GIGABYTE MD61-SC2-00 v01000100 (T15 BIOS) and llvmpipe on Ubuntu 21.04 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 2103273-IB-2103266IB69
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AV1 3 Tests
C/C++ Compiler Tests 6 Tests
Compression Tests 2 Tests
CPU Massive 12 Tests
Creator Workloads 14 Tests
Encoding 5 Tests
Fortran Tests 2 Tests
Game Development 3 Tests
HPC - High Performance Computing 9 Tests
Machine Learning 4 Tests
Molecular Dynamics 3 Tests
MPI Benchmarks 3 Tests
Multi-Core 19 Tests
NVIDIA GPU Compute 5 Tests
Intel oneAPI 5 Tests
OpenMPI Tests 4 Tests
Programmer / Developer System Benchmarks 2 Tests
Renderers 4 Tests
Scientific Computing 3 Tests
Server CPU Tests 11 Tests
Video Encoding 5 Tests
Common Workstation Benchmarks 2 Tests

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Clear Linux 34420
March 26 2021
  5 Hours, 57 Minutes
Ubuntu 21.04 Dev
March 26 2021
  8 Hours, 35 Minutes
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  7 Hours, 16 Minutes
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Cascade Lake Clear Linux 2021 Suite 1.0.0 System Test suite extracted from Cascade Lake Clear Linux 2021. pts/dav1d-1.8.0 -i chimera_8b_1080p.ivf Video Input: Chimera 1080p pts/dav1d-1.8.0 -i summer_nature_4k.ivf Video Input: Summer Nature 4K pts/dav1d-1.8.0 -i summer_nature_1080p.ivf Video Input: Summer Nature 1080p pts/dav1d-1.8.0 -i chimera_10b_1080p.ivf Video Input: Chimera 1080p 10-bit pts/ospray-1.0.3 sanm/sanm.obj -vp 22.958788 3.204613 2.712676 -vu 0.000000 1.000000 0.000000 -vi 12.364944 0.176316 4.009342 -sg:sun:intensity=4.0 -sg:sun:direction=0,-1,0 -sg:bounce:intensity=0.0 --hdri-light rnl_probe.pfm -sg:hdri:intensity=1.25 --renderer pathtracer Demo: San Miguel - Renderer: Path Tracer pts/ospray-1.0.3 xfrog-forest.xml --renderer pathtracer Demo: XFrog Forest - Renderer: Path Tracer pts/ospray-1.0.3 NASA-B-field-sun.osx --renderer pathtracer Demo: NASA Streamlines - Renderer: Path Tracer pts/ospray-1.0.3 magnetic-512-volume/magnetic-512-volume.osp --renderer pathtracer Demo: Magnetic Reconnection - Renderer: Path Tracer pts/embree-1.1.1 pathtracer -c crown/crown.ecs Binary: Pathtracer - Model: Crown pts/embree-1.1.1 pathtracer_ispc -c crown/crown.ecs Binary: Pathtracer ISPC - Model: Crown pts/embree-1.1.1 pathtracer -c asian_dragon/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon pts/embree-1.1.1 pathtracer_ispc -c asian_dragon/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon pts/svt-av1-2.2.1 -enc-mode 0 -n 20 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Enc Mode 0 - Input: 1080p pts/svt-av1-2.2.1 -enc-mode 4 -n 80 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Enc Mode 4 - Input: 1080p pts/svt-av1-2.2.1 -enc-mode 8 -n 320 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Enc Mode 8 - Input: 1080p pts/svt-hevc-1.2.0 -encMode 1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: 1 - Input: Bosphorus 1080p pts/svt-hevc-1.2.0 -encMode 7 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: 7 - Input: Bosphorus 1080p pts/svt-hevc-1.2.0 -encMode 10 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: 10 - Input: Bosphorus 1080p pts/svt-vp9-1.3.0 -tune 2 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: VMAF Optimized - Input: Bosphorus 1080p pts/svt-vp9-1.3.0 -tune 1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p pts/svt-vp9-1.3.0 -tune 0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p pts/simdjson-1.2.0 kostya Throughput Test: Kostya pts/simdjson-1.2.0 large_random Throughput Test: LargeRandom pts/simdjson-1.2.0 partial_tweets Throughput Test: PartialTweets pts/simdjson-1.2.0 distinct_user_id Throughput Test: DistinctUserID pts/oidn-1.2.0 -hdr memorial.pfm Scene: Memorial pts/openvkl-1.0.0 vklBenchmark Benchmark: vklBenchmark pts/indigobench-1.1.0 --cpuonly --scenes bedroom Acceleration: CPU - Scene: Bedroom pts/indigobench-1.1.0 --cpuonly --scenes supercar Acceleration: CPU - Scene: Supercar pts/compress-lz4-1.0.0 -b3 -e3 Compression Level: 3 - Compression Speed pts/compress-lz4-1.0.0 -b3 -e3 Compression Level: 3 - Decompression Speed pts/compress-lz4-1.0.0 -b9 -e9 Compression Level: 9 - Compression Speed pts/compress-lz4-1.0.0 -b9 -e9 Compression Level: 9 - Decompression Speed pts/compress-zstd-1.3.0 -b19 Compression Level: 19 - Compression Speed pts/compress-zstd-1.3.0 -b19 Compression Level: 19 - Decompression Speed pts/compress-zstd-1.3.0 -b8 --long Compression Level: 8, Long Mode - Compression Speed pts/compress-zstd-1.3.0 -b19 --long Compression Level: 19, Long Mode - Compression Speed pts/compress-zstd-1.3.0 -b19 --long Compression Level: 19, Long Mode - Decompression Speed pts/compress-zstd-1.3.0 -b8 --long Compression Level: 8, Long Mode - Decompression Speed pts/stockfish-1.3.0 Total Time pts/gromacs-1.5.0 water_GMX50_bare Input: water_GMX50_bare pts/liquid-dsp-1.0.0 -n 1 -b 256 -f 57 Threads: 1 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.0.0 -n 16 -b 256 -f 57 Threads: 16 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.0.0 -n 32 -b 256 -f 57 Threads: 32 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.0.0 -n 64 -b 256 -f 57 Threads: 64 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.0.0 -n 112 -b 256 -f 57 Threads: 112 - Buffer Length: 256 - Filter Length: 57 pts/npb-1.4.2 ep.D Test / Class: EP.D pts/npb-1.4.2 lu.C Test / Class: LU.C pts/synthmark-1.0.0 -tv -p100 -s30 Test: VoiceMark_100 pts/v-ray-1.3.0 -m vray Mode: CPU pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms pts/tensorflow-lite-1.0.0 --graph=squeezenet.tflite Model: SqueezeNet pts/tensorflow-lite-1.0.0 --graph=inception_v4.tflite Model: Inception V4 pts/tensorflow-lite-1.0.0 --graph=nasnet_mobile.tflite Model: NASNet Mobile pts/tensorflow-lite-1.0.0 --graph=mobilenet_v1_1.0_224.tflite Model: Mobilenet Float pts/tensorflow-lite-1.0.0 --graph=mobilenet_v1_1.0_224_quant.tflite Model: Mobilenet Quant pts/tensorflow-lite-1.0.0 --graph=inception_resnet_v2.tflite Model: Inception ResNet V2 pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU pts/mnn-1.2.0 Model: SqueezeNetV1.0 pts/mnn-1.2.0 Model: resnet-v2-50 pts/mnn-1.2.0 Model: MobileNetV2_224 pts/mnn-1.2.0 Model: mobilenet-v1-1.0 pts/mnn-1.2.0 Model: inception-v3 pts/tnn-1.0.1 -dt NAIVE -mp ../benchmark/benchmark-model/mobilenet_v2.tnnproto Target: CPU - Model: MobileNet v2 pts/tnn-1.0.1 -dt NAIVE -mp ../benchmark/benchmark-model/squeezenet_v1.1.tnnproto Target: CPU - Model: SqueezeNet v1.1 pts/rodinia-1.3.1 OMP_LAVAMD Test: OpenMP LavaMD pts/rodinia-1.3.1 OMP_HOTSPOT3D Test: OpenMP HotSpot3D pts/rodinia-1.3.1 OMP_LEUKOCYTE Test: OpenMP Leukocyte pts/rodinia-1.3.1 OMP_CFD Test: OpenMP CFD Solver pts/rodinia-1.3.1 OMP_STREAMCLUSTER Test: OpenMP Streamcluster pts/incompact3d-2.0.2 input.i3d Input: X3D-benchmarking input.i3d pts/incompact3d-2.0.2 input_129_nodes.i3d Input: input.i3d 129 Cells Per Direction pts/incompact3d-2.0.2 input_193_nodes.i3d Input: input.i3d 193 Cells Per Direction pts/avifenc-1.1.1 -s 2 Encoder Speed: 2 pts/avifenc-1.1.1 -s 6 Encoder Speed: 6 pts/avifenc-1.1.1 -s 10 Encoder Speed: 10 pts/avifenc-1.1.1 -s 6 -l Encoder Speed: 6, Lossless pts/avifenc-1.1.1 -s 10 -l Encoder Speed: 10, Lossless pts/blender-1.9.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: BMW27 - Compute: CPU-Only pts/blender-1.9.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Fishy Cat - Compute: CPU-Only