Skylake Core i5 7600K

Intel Core i5-7600K testing with a Gigabyte Z270M-D3H-CF (F8d BIOS) and Gigabyte Intel HD 630 3GB on Ubuntu 20.04 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 2009288-FI-SKYLAKECO89
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AV1 2 Tests
Bioinformatics 2 Tests
BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
C/C++ Compiler Tests 6 Tests
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CPU Massive 8 Tests
Creator Workloads 7 Tests
Database Test Suite 2 Tests
Encoding 2 Tests
Fortran Tests 5 Tests
HPC - High Performance Computing 17 Tests
Imaging 4 Tests
Machine Learning 8 Tests
Molecular Dynamics 5 Tests
MPI Benchmarks 4 Tests
Multi-Core 6 Tests
NVIDIA GPU Compute 4 Tests
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Python Tests 3 Tests
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Single-Threaded 4 Tests
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Linux 5.4
September 27 2020
  8 Hours, 39 Minutes
Linux 5.8
September 28 2020
  8 Hours, 47 Minutes
Linux 5.9-rc7
September 28 2020
  8 Hours, 4 Minutes
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  8 Hours, 30 Minutes

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Skylake Core i5 7600K Suite 1.0.0 System Test suite extracted from Skylake Core i5 7600K. pts/couchdb-1.0.1 100 1000 24 Bulk Size: 100 - Inserts: 1000 - Rounds: 24 pts/mlpack-1.0.2 SCIKIT_ICA Benchmark: scikit_ica pts/ffte-1.2.0 N=256, 3D Complex FFT Routine pts/lczero-1.5.1 -b blas Backend: BLAS pts/influxdb-1.0.0 -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/mafft-1.6.1 Multiple Sequence Alignment - LSU RNA pts/byte-1.2.2 TEST_DHRY2 Computational Test: Dhrystone 2 pts/influxdb-1.0.0 -c 64 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/glmark2-1.2.0 -s 1920x1080 Resolution: 1920 x 1080 pts/gromacs-1.4.0 Water Benchmark pts/ncnn-1.0.3 -1 Target: CPU - Model: squeezenet pts/mnn-1.0.1 Model: mobilenet-v1-1.0 pts/compress-zstd-1.2.1 -b3 Compression Level: 3 pts/tnn-1.0.0 -dt NAIVE -mp ../benchmark/benchmark-model/mobilenet_v2.tnnproto Target: CPU - Model: MobileNet v2 pts/espeak-1.6.0 Text-To-Speech Synthesis pts/ncnn-1.0.3 -1 Target: CPU - Model: blazeface pts/ncnn-1.0.3 -1 Target: CPU - Model: shufflenet-v2 pts/lczero-1.5.1 -b eigen Backend: Eigen pts/ncnn-1.0.3 -1 Target: CPU - Model: efficientnet-b0 pts/webp-1.0.0 -q 100 -lossless Encode Settings: Quality 100, Lossless system/mpv-1.0.1 bbb_sunflower_1080p_30fps_normal.mp4 --hwdec=no Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only pts/mnn-1.0.1 Model: inception-v3 pts/ncnn-1.0.3 -1 Target: CPU - Model: mobilenet pts/ncnn-1.0.3 -1 Target: CPU-v3-v3 - Model: mobilenet-v3 pts/hint-1.0.3 FLOAT Test: FLOAT pts/ncnn-1.0.3 -1 Target: CPU - Model: googlenet pts/mnn-1.0.1 Model: MobileNetV2_224 system/mpv-1.0.1 bbb_sunflower_2160p_30fps_normal.mp4 --hwdec=no Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only pts/ncnn-1.0.3 -1 Target: CPU - Model: yolov4-tiny pts/aom-av1-2.1.2 --cpu-used=8 --rt Encoder Mode: Speed 8 Realtime pts/ncnn-1.0.3 -1 Target: CPU - Model: alexnet pts/webp-1.0.0 -q 100 -m 6 Encode Settings: Quality 100, Highest Compression pts/ncnn-1.0.3 -1 Target: CPU - Model: vgg16 pts/system-decompress-gzip-1.1.1 pts/ncnn-1.0.3 -1 Target: CPU - Model: resnet18 pts/ncnn-1.0.3 -1 Target: CPU - Model: resnet50 pts/mlpack-1.0.2 SCIKIT_LINEARRIDGEREGRESSION Benchmark: scikit_linearridgeregression pts/lczero-1.5.1 -b random Backend: Random pts/mnn-1.0.1 Model: SqueezeNetV1.0 pts/astcenc-1.0.0 -fast Preset: Fast pts/tnn-1.0.0 -dt NAIVE -mp ../benchmark/benchmark-model/squeezenet_v1.1.tnnproto Target: CPU - Model: SqueezeNet v1.1 pts/lammps-1.2.1 in.rhodo Model: Rhodopsin Protein pts/dcraw-1.1.1 RAW To PPM Image Conversion pts/mnn-1.0.1 Model: resnet-v2-50 pts/avifenc-1.0.0 -s 10 Encoder Speed: 10 pts/dolfyn-1.0.3 Computational Fluid Dynamics pts/webp-1.0.0 Encode Settings: Default pts/avifenc-1.0.0 -s 2 Encoder Speed: 2 pts/avifenc-1.0.0 -s 8 Encoder Speed: 8 pts/hmmer-1.2.0 Pfam Database Search pts/webp-1.0.0 -q 100 Encode Settings: Quality 100 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -iterations 100 Model: GoogleNet - Acceleration: CPU - Iterations: 100 pts/webp-1.0.0 -q 100 -lossless -m 6 Encode Settings: Quality 100, Lossless, Highest Compression pts/mocassin-1.0.0 Input: Dust 2D tau100.0 pts/incompact3d-1.0.0 examples/Cylinder/input.i3d Input: Cylinder pts/aom-av1-2.1.2 --cpu-used=6 --limit=80 Encoder Mode: Speed 6 Two-Pass pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms pts/ncnn-1.0.3 -1 Target: CPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.0.3 -1 Target: CPU - Model: mnasnet pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -iterations 200 Model: GoogleNet - Acceleration: CPU - Iterations: 200 pts/libraw-1.0.0 Post-Processing Benchmark pts/aom-av1-2.1.2 --cpu-used=6 --rt Encoder Mode: Speed 6 Realtime pts/mlpack-1.0.2 SCIKIT_SVM Benchmark: scikit_svm pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -iterations 200 Model: AlexNet - Acceleration: CPU - Iterations: 200 pts/astcenc-1.0.0 -medium Preset: Medium pts/astcenc-1.0.0 -exhaustive Preset: Exhaustive pts/avifenc-1.0.0 -s 0 Encoder Speed: 0 pts/astcenc-1.0.0 -thorough Preset: Thorough pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -iterations 100 Model: AlexNet - Acceleration: CPU - Iterations: 100 pts/tensorflow-lite-1.0.0 --graph=nasnet_mobile.tflite Model: NASNet Mobile pts/tensorflow-lite-1.0.0 --graph=inception_resnet_v2.tflite Model: Inception ResNet V2 pts/tensorflow-lite-1.0.0 --graph=squeezenet.tflite Model: SqueezeNet pts/tensorflow-lite-1.0.0 --graph=mobilenet_v1_1.0_224.tflite Model: Mobilenet Float pts/tensorflow-lite-1.0.0 --graph=inception_v4.tflite Model: Inception V4 pts/tensorflow-lite-1.0.0 --graph=mobilenet_v1_1.0_224_quant.tflite Model: Mobilenet Quant pts/aom-av1-2.1.2 --cpu-used=4 --limit=40 Encoder Mode: Speed 4 Two-Pass pts/aom-av1-2.1.2 --cpu-used=0 --limit=10 Encoder Mode: Speed 0 Two-Pass pts/compress-zstd-1.2.1 -b19 Compression Level: 19 pts/influxdb-1.0.0 -c 1024 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/opencv-1.0.0 dnn Test: DNN - Deep Neural Network pts/mlpack-1.0.2 SCIKIT_QDA Benchmark: scikit_qda