Core i7 4770K Xmas

Intel Core i7-4770K testing with a Gigabyte Z97-HD3 (F10c BIOS) and Gigabyte Intel HD 4600 2GB on Ubuntu 20.10 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 2012256-HA-COREI747702
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Audio Encoding 3 Tests
Timed Code Compilation 3 Tests
C/C++ Compiler Tests 4 Tests
CPU Massive 4 Tests
Creator Workloads 5 Tests
Encoding 3 Tests
HPC - High Performance Computing 3 Tests
Machine Learning 2 Tests
Multi-Core 5 Tests
Programmer / Developer System Benchmarks 6 Tests
Server 3 Tests

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December 25 2020
  5 Hours, 48 Minutes
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December 25 2020
  5 Hours, 39 Minutes
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December 25 2020
  5 Hours, 54 Minutes
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  5 Hours, 47 Minutes

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Core i7 4770K Xmas Intel Core i7-4770K testing with a Gigabyte Z97-HD3 (F10c BIOS) and Gigabyte Intel HD 4600 2GB on Ubuntu 20.10 via the Phoronix Test Suite. ,,"1","2","3" Processor,,Intel Core i7-4770K @ 3.90GHz (4 Cores / 8 Threads),Intel Core i7-4770K @ 3.90GHz (4 Cores / 8 Threads),Intel Core i7-4770K @ 3.90GHz (4 Cores / 8 Threads) Motherboard,,Gigabyte Z97-HD3 (F10c BIOS),Gigabyte Z97-HD3 (F10c BIOS),Gigabyte Z97-HD3 (F10c BIOS) Chipset,,Intel 4th Gen Core DRAM,Intel 4th Gen Core DRAM,Intel 4th Gen Core DRAM Memory,,8GB,8GB,8GB Disk,,120GB ADATA SU700,120GB ADATA SU700,120GB ADATA SU700 Graphics,,Gigabyte Intel HD 4600 2GB (1250MHz),Gigabyte Intel HD 4600 2GB (1250MHz),Gigabyte Intel HD 4600 2GB (1250MHz) Audio,,Intel Xeon E3-1200 v3/4th,Intel Xeon E3-1200 v3/4th,Intel Xeon E3-1200 v3/4th Monitor,,DELL S2409W,DELL S2409W,DELL S2409W Network,,Realtek RTL8111/8168/8411,Realtek RTL8111/8168/8411,Realtek RTL8111/8168/8411 OS,,Ubuntu 20.10,Ubuntu 20.10,Ubuntu 20.10 Kernel,,5.8.0-31-generic (x86_64),5.8.0-31-generic (x86_64),5.8.0-31-generic (x86_64) Desktop,,GNOME Shell 3.38.1,GNOME Shell 3.38.1,GNOME Shell 3.38.1 Display Server,,X Server 1.20.9,X Server 1.20.9,X Server 1.20.9 Display Driver,,modesetting 1.20.9,modesetting 1.20.9,modesetting 1.20.9 OpenGL,,4.5 Mesa 20.2.1,4.5 Mesa 20.2.1,4.5 Mesa 20.2.1 Vulkan,,1.2.145,1.2.145,1.2.145 Compiler,,GCC 10.2.0,GCC 10.2.0,GCC 10.2.0 File-System,,ext4,ext4,ext4 Screen Resolution,,1920x1080,1920x1080,1920x1080 ,,"1","2","3" "CLOMP - Static OMP Speedup (Speedup)",HIB,0.9,1.1,1.1 "Build2 - Time To Compile (sec)",LIB,388.393,385.584,388.953 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,42373,42365,42169 "Timed FFmpeg Compilation - Time To Compile (sec)",LIB,145.942,146.295,146.978 "Timed HMMer Search - Pfam Database Search (sec)",LIB,137.774,137.939,137.903 "NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,20.70,20.75,20.88 "NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,40.27,41.27,42.10 "NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,51.83,53.05,53.45 "NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,63.21,63.55,63.34 "NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,25.09,25.62,25.11 "NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,30.47,30.64,30.69 "NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,126.48,128.34,127.97 "NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,29.81,30.53,30.37 "NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,3.25,3.18,3.24 "NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,14.40,14.28,14.26 "NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,8.53,8.41,8.43 "NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,11.51,11.42,11.49 "NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,8.77,8.72,8.84 "NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,10.56,10.50,10.89 "NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,39.24,39.55,39.64 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,20.69,20.55,20.90 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,40.61,40.30,41.57 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,51.58,52.98,54.23 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,61.85,63.27,64.10 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,25.10,25.16,25.17 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,30.48,31.42,30.75 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,127.46,127.55,128.02 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,29.65,30.43,30.19 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,3.29,3.17,3.28 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,14.26,14.32,14.43 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,8.37,8.42,8.65 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,11.41,11.42,11.44 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,8.74,8.66,8.91 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,10.42,10.66,11.04 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,39.30,39.29,39.77 "VKMark - Resolution: 1920 x 1080 (VKMark Score)",HIB,292,292,290 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,10641.5,10647.0,10925.1 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,10639.4,10420.8,10853.5 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,10419.2,10472.4,10683.5 "Timed Eigen Compilation - Time To Compile (sec)",LIB,96.656,97.289,97.299 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5730.72,5954.52,6041.90 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,5784.04,5922.99,5971.44 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5907.30,5822.13,5981.80 "Node.js V8 Web Tooling Benchmark - (runs/s)",HIB,9.30,9.29,9.24 "SQLite Speedtest - Timed Time - Size 1,000 (sec)",LIB,80.186,81.524,80.100 "simdjson - Throughput Test: Kostya (GB/s)",HIB,0.60,0.60,0.60 "simdjson - Throughput Test: LargeRandom (GB/s)",HIB,0.4,0.4,0.4 "simdjson - Throughput Test: DistinctUserID (GB/s)",HIB,0.68,0.68,0.68 "simdjson - Throughput Test: PartialTweets (GB/s)",HIB,0.66,0.66,0.66 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,14.4191,14.8307,14.5672 "Coremark - CoreMark Size 666 - Iterations Per Second (Iterations/Sec)",HIB,144430.967517,144054.759207,144381.891641 "WavPack Audio Encoding - WAV To WavPack (sec)",LIB,15.548,15.544,15.562 "Monkey Audio Encoding - WAV To APE (sec)",LIB,14.059,13.873,13.953 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,8.10435,8.09766,8.85443 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,13.5497,13.3557,13.2922 "oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,15.9142,15.6513,18.8928 "Opus Codec Encoding - WAV To Opus Encode (sec)",LIB,9.132,9.133,9.113 "oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,11.1734,11.3617,11.5933 "oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5.97793,5.94146,5.99872 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7.32951,7.33567,7.23631 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.72613,4.69355,4.99786 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,31.0265,30.9250,30.9474 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,32.1198,32.1261,32.5780 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,12.9561,12.9542,12.9019 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,18.9265,18.9535,19.0737