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