Intel Core i5-6500 testing with a Gigabyte Z170M-D3H-CF (F22f BIOS) and Gigabyte Intel HD 530 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 2009292-FI-SKYLAKECO34
Skylake Core i5 6500
Intel Core i5-6500 testing with a Gigabyte Z170M-D3H-CF (F22f BIOS) and Gigabyte Intel HD 530 3GB on Ubuntu 20.04 via the Phoronix Test Suite.
,,"Linux 5.4","Linux 5.8.12","Linux 5.9-rc7"
Processor,,Intel Core i5-6500 @ 3.60GHz (4 Cores),Intel Core i5-6500 @ 3.60GHz (4 Cores),Intel Core i5-6500 @ 3.60GHz (4 Cores)
Motherboard,,Gigabyte Z170M-D3H-CF (F22f BIOS),Gigabyte Z170M-D3H-CF (F22f BIOS),Gigabyte Z170M-D3H-CF (F22f BIOS)
Chipset,,Intel Xeon E3-1200 v5/E3-1500,Intel Xeon E3-1200 v5/E3-1500,Intel Xeon E3-1200 v5/E3-1500
Memory,,8GB,8GB,8GB
Disk,,250GB Samsung SSD 850,250GB Samsung SSD 850,250GB Samsung SSD 850
Graphics,,Gigabyte Intel HD 530 3GB (1050MHz),Gigabyte Intel HD 530 3GB (1050MHz),Gigabyte Intel HD 530 3GB (1050MHz)
Audio,,Realtek ALC892,Realtek ALC892,Realtek ALC892
Monitor,,G237HL,G237HL,G237HL
Network,,Intel I219-V,Intel I219-V,Intel I219-V
OS,,Ubuntu 20.04,Ubuntu 20.04,Ubuntu 20.04
Kernel,,5.4.0-45-generic (x86_64),5.8.12-050812-generic (x86_64),5.9.0-050900rc7daily20200929-generic (x86_64) 20200928
Desktop,,GNOME Shell 3.36.4,GNOME Shell 3.36.4,GNOME Shell 3.36.4
Display Server,,X Server 1.20.8,X Server 1.20.8,X Server 1.20.8
Display Driver,,modesetting 1.20.8,modesetting 1.20.8,modesetting 1.20.8
OpenGL,,4.6 Mesa 20.0.4,4.6 Mesa 20.0.4,4.6 Mesa 20.0.4
OpenCL,,OpenCL 2.1,OpenCL 2.1,OpenCL 2.1
Compiler,,GCC 9.3.0,GCC 9.3.0,GCC 9.3.0
File-System,,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080
,,"Linux 5.4","Linux 5.8.12","Linux 5.9-rc7"
"MPV - Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only (FPS)",HIB,74.83,75.21,75.22
"MPV - Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only (FPS)",HIB,204.04,207.08,206.86
"AOM AV1 - Encoder Mode: Speed 6 Realtime (FPS)",HIB,12.96,12.98,12.95
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass (FPS)",HIB,2.69,2.69,2.68
"AOM AV1 - Encoder Mode: Speed 8 Realtime (FPS)",HIB,32.84,32.63,32.72
"BYTE Unix Benchmark - Computational Test: Dhrystone 2 (LPS)",HIB,35634715.8,35578653.6,35158099.5
"FFTE - N=256, 3D Complex FFT Routine (MFLOPS)",HIB,17566.367941500,17695.538070112,17854.791823564
"LibRaw - Post-Processing Benchmark (Mpix/sec)",HIB,23.08,23.05,23.06
"LeelaChessZero - Backend: BLAS (Nodes/s)",HIB,852,834,827
"LeelaChessZero - Backend: Eigen (Nodes/s)",HIB,810,759,789
"GROMACS - Water Benchmark (Ns/Day)",HIB,0.469,0.466,0.472
"LAMMPS Molecular Dynamics Simulator - Model: Rhodopsin Protein (ns/day)",HIB,2.533,2.536,2.525
"KeyDB - (Ops/sec)",HIB,241149.57,242725.17,244927.94
"Hierarchical INTegration - Test: FLOAT (QUIPs)",HIB,361421279.16012,359752768.98517,359707021.11346
"GLmark2 - Resolution: 1920 x 1080 (Score)",HIB,484,498,499
"InfluxDB - Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 (val/sec)",HIB,875726.3,848096.4,847939.2
"InfluxDB - Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 (val/sec)",HIB,899170.0,881495.6,887270.8
"NAMD - ATPase Simulation - 327,506 Atoms (days/ns)",LIB,4.98990,5.00306,4.98427
"WebP Image Encode - Encode Settings: Default (Encode Time - sec)",LIB,1.874,1.893,1.880
"WebP Image Encode - Encode Settings: Quality 100 (Encode Time - sec)",LIB,2.942,2.957,2.959
"WebP Image Encode - Encode Settings: Quality 100, Lossless (Encode Time - sec)",LIB,21.606,21.834,21.697
"WebP Image Encode - Encode Settings: Quality 100, Highest Compression (Encode Time - sec)",LIB,8.786,8.833,8.823
"WebP Image Encode - Encode Settings: Quality 100, Lossless, Highest Compression (Encode Time - sec)",LIB,53.058,53.228,53.306
"Caffe - Model: AlexNet - Acceleration: CPU - Iterations: 100 (ms)",LIB,38264,38284,38398
"Caffe - Model: GoogleNet - Acceleration: CPU - Iterations: 100 (ms)",LIB,93409,93347,93209
"Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,8.523,8.523,8.523
"Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,37.345,37.198,37.289
"Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,4.952,4.957,4.951
"Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,6.351,6.344,6.348
"Mobile Neural Network - Model: inception-v3 (ms)",LIB,50.422,50.436,50.404
"NCNN - Target: CPU - Model: squeezenet (ms)",LIB,27.13,27.18,27.18
"NCNN - Target: CPU - Model: mobilenet (ms)",LIB,31.35,31.35,31.34
"NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,7.98,7.99,7.97
"NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,7.04,7.09,7.07
"NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,4.98,5.00,5.00
"NCNN - Target: CPU - Model: mnasnet (ms)",LIB,7.18,7.20,7.18
"NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,11.37,11.40,11.39
"NCNN - Target: CPU - Model: blazeface (ms)",LIB,1.96,1.96,1.96
"NCNN - Target: CPU - Model: googlenet (ms)",LIB,27.20,27.25,27.25
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,97.23,98.29,98.00
"NCNN - Target: CPU - Model: resnet18 (ms)",LIB,28.12,28.13,28.14
"NCNN - Target: CPU - Model: alexnet (ms)",LIB,25.85,25.94,25.92
"NCNN - Target: CPU - Model: resnet50 (ms)",LIB,53.29,53.31,53.32
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,46.19,46.33,46.27
"NCNN - Target: Vulkan GPU - Model: squeezenet (ms)",LIB,106.56,47.62,47.60
"NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,98.34,41.73,41.18
"NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,33.67,13.51,13.52
"NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,37.84,14.92,14.94
"NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,23.21,9.41,11.23
"NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,34.91,13.91,13.92
"NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,70.82,28.10,28.11
"NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,6.47,3.45,3.19
"NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,91.34,38.51,38.50
"NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,280.10,231.43,232.40
"NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,79.88,34.03,34.04
"NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,106.85,53.67,54.56
"NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,146.09,82.22,82.20
"NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,145.04,81.87,81.88
"TNN - Target: CPU - Model: MobileNet v2 (ms)",LIB,377.119,373.414,374.253
"TNN - Target: CPU - Model: SqueezeNet v1.1 (ms)",LIB,372.485,375.855,374.335
"OpenCV - Test: DNN - Deep Neural Network (ms)",LIB,38827,23997,23722
"RealSR-NCNN - Scale: 4x - TAA: No (sec)",LIB,17.282,303.112,301.102
"Dolfyn - Computational Fluid Dynamics (sec)",LIB,23.366,23.420,23.466
"Timed HMMer Search - Pfam Database Search (sec)",LIB,130.872,130.644,130.974
"Incompact3D - Input: Cylinder (sec)",LIB,813.295349,815.482341,812.175049
"Timed MAFFT Alignment - Multiple Sequence Alignment - LSU RNA (sec)",LIB,12.893,12.743,12.832
"Monte Carlo Simulations of Ionised Nebulae - Input: Dust 2D tau100.0 (sec)",LIB,329,329,329
"eSpeak-NG Speech Engine - Text-To-Speech Synthesis (sec)",LIB,33.998,34.471,33.888
"System GZIP Decompression - (sec)",LIB,3.577,3.591,3.583
"Apache CouchDB - Bulk Size: 100 - Inserts: 1000 - Rounds: 24 (sec)",LIB,232.895,209.267,208.272
"Mlpack Benchmark - Benchmark: scikit_ica (sec)",LIB,60.22,62.46,60.88
"Mlpack Benchmark - Benchmark: scikit_qda (sec)",LIB,80.48,80.38,80.15
"Mlpack Benchmark - Benchmark: scikit_svm (sec)",LIB,29.53,29.47,29.51
"Mlpack Benchmark - Benchmark: scikit_linearridgeregression (sec)",LIB,5.14,4.57,4.56