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.

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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
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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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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: Processor: Intel Core i7-4770K @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Gigabyte Z97-HD3 (F10c BIOS), Chipset: Intel 4th Gen Core DRAM, Memory: 8GB, Disk: 120GB ADATA SU700, Graphics: Gigabyte Intel HD 4600 2GB (1250MHz), Audio: Intel Xeon E3-1200 v3/4th, Monitor: DELL S2409W, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.10, Kernel: 5.8.0-31-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.5 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Core i7-4770K @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Gigabyte Z97-HD3 (F10c BIOS), Chipset: Intel 4th Gen Core DRAM, Memory: 8GB, Disk: 120GB ADATA SU700, Graphics: Gigabyte Intel HD 4600 2GB (1250MHz), Audio: Intel Xeon E3-1200 v3/4th, Monitor: DELL S2409W, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.10, Kernel: 5.8.0-31-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.5 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Core i7-4770K @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Gigabyte Z97-HD3 (F10c BIOS), Chipset: Intel 4th Gen Core DRAM, Memory: 8GB, Disk: 120GB ADATA SU700, Graphics: Gigabyte Intel HD 4600 2GB (1250MHz), Audio: Intel Xeon E3-1200 v3/4th, Monitor: DELL S2409W, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.10, Kernel: 5.8.0-31-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.5 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 BRL-CAD 7.30.8 VGR Performance Metric VGR Performance Metric > Higher Is Better 1 . 42373 |==================================================================== 2 . 42365 |==================================================================== 3 . 42169 |==================================================================== Build2 0.13 Time To Compile Seconds < Lower Is Better 1 . 388.39 |=================================================================== 2 . 385.58 |================================================================== 3 . 388.95 |=================================================================== CLOMP 1.2 Static OMP Speedup Speedup > Higher Is Better 1 . 0.9 |========================================================= 2 . 1.1 |====================================================================== 3 . 1.1 |====================================================================== Coremark 1.0 CoreMark Size 666 - Iterations Per Second Iterations/Sec > Higher Is Better 1 . 144430.97 |================================================================ 2 . 144054.76 |================================================================ 3 . 144381.89 |================================================================ Monkey Audio Encoding 3.99.6 WAV To APE Seconds < Lower Is Better 1 . 14.06 |==================================================================== 2 . 13.87 |=================================================================== 3 . 13.95 |=================================================================== NCNN 20201218 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 39.30 |=================================================================== 2 . 39.29 |=================================================================== 3 . 39.77 |==================================================================== NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 10.42 |================================================================ 2 . 10.66 |================================================================== 3 . 11.04 |==================================================================== NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 8.74 |==================================================================== 2 . 8.66 |=================================================================== 3 . 8.91 |===================================================================== NCNN 20201218 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 11.41 |==================================================================== 2 . 11.42 |==================================================================== 3 . 11.44 |==================================================================== NCNN 20201218 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 8.37 |=================================================================== 2 . 8.42 |=================================================================== 3 . 8.65 |===================================================================== NCNN 20201218 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 14.26 |=================================================================== 2 . 14.32 |=================================================================== 3 . 14.43 |==================================================================== NCNN 20201218 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 3.29 |===================================================================== 2 . 3.17 |================================================================== 3 . 3.28 |===================================================================== NCNN 20201218 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 29.65 |================================================================== 2 . 30.43 |==================================================================== 3 . 30.19 |=================================================================== NCNN 20201218 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 127.46 |=================================================================== 2 . 127.55 |=================================================================== 3 . 128.02 |=================================================================== NCNN 20201218 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 30.48 |================================================================== 2 . 31.42 |==================================================================== 3 . 30.75 |=================================================================== NCNN 20201218 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 25.10 |==================================================================== 2 . 25.16 |==================================================================== 3 . 25.17 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 61.85 |================================================================== 2 . 63.27 |=================================================================== 3 . 64.10 |==================================================================== NCNN 20201218 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 51.58 |================================================================= 2 . 52.98 |================================================================== 3 . 54.23 |==================================================================== NCNN 20201218 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 40.61 |================================================================== 2 . 40.30 |================================================================== 3 . 41.57 |==================================================================== NCNN 20201218 Target: CPU - Model: regnety_400m ms < Lower Is Better 1 . 20.69 |=================================================================== 2 . 20.55 |=================================================================== 3 . 20.90 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better 1 . 39.24 |=================================================================== 2 . 39.55 |==================================================================== 3 . 39.64 |==================================================================== NCNN 20201218 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 10.56 |================================================================== 2 . 10.50 |================================================================== 3 . 10.89 |==================================================================== NCNN 20201218 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 8.77 |==================================================================== 2 . 8.72 |==================================================================== 3 . 8.84 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 11.51 |==================================================================== 2 . 11.42 |=================================================================== 3 . 11.49 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better 1 . 8.53 |===================================================================== 2 . 8.41 |==================================================================== 3 . 8.43 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 14.40 |==================================================================== 2 . 14.28 |=================================================================== 3 . 14.26 |=================================================================== NCNN 20201218 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better 1 . 3.25 |===================================================================== 2 . 3.18 |==================================================================== 3 . 3.24 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better 1 . 29.81 |================================================================== 2 . 30.53 |==================================================================== 3 . 30.37 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better 1 . 126.48 |================================================================== 2 . 128.34 |=================================================================== 3 . 127.97 |=================================================================== NCNN 20201218 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better 1 . 30.47 |==================================================================== 2 . 30.64 |==================================================================== 3 . 30.69 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better 1 . 25.09 |=================================================================== 2 . 25.62 |==================================================================== 3 . 25.11 |=================================================================== NCNN 20201218 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better 1 . 63.21 |==================================================================== 2 . 63.55 |==================================================================== 3 . 63.34 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better 1 . 51.83 |================================================================== 2 . 53.05 |=================================================================== 3 . 53.45 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 40.27 |================================================================= 2 . 41.27 |=================================================================== 3 . 42.10 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: regnety_400m ms < Lower Is Better 1 . 20.70 |=================================================================== 2 . 20.75 |==================================================================== 3 . 20.88 |==================================================================== Node.js V8 Web Tooling Benchmark runs/s > Higher Is Better 1 . 9.30 |===================================================================== 2 . 9.29 |===================================================================== 3 . 9.24 |===================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 11.17 |================================================================== 2 . 11.36 |=================================================================== 3 . 11.59 |==================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 15.91 |========================================================= 2 . 15.65 |======================================================== 3 . 18.89 |==================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.97793 |================================================================== 2 . 5.94146 |================================================================= 3 . 5.99872 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.72613 |============================================================== 2 . 4.69355 |============================================================== 3 . 4.99786 |================================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 32.12 |=================================================================== 2 . 32.13 |=================================================================== 3 . 32.58 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 13.55 |==================================================================== 2 . 13.36 |=================================================================== 3 . 13.29 |=================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 18.93 |==================================================================== 2 . 18.95 |==================================================================== 3 . 19.07 |==================================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 31.03 |==================================================================== 2 . 30.93 |==================================================================== 3 . 30.95 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 14.42 |================================================================== 2 . 14.83 |==================================================================== 3 . 14.57 |=================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 12.96 |==================================================================== 2 . 12.95 |==================================================================== 3 . 12.90 |==================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 10419.2 |================================================================ 2 . 10472.4 |================================================================= 3 . 10683.5 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5784.04 |================================================================ 2 . 5922.99 |================================================================= 3 . 5971.44 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 10639.4 |================================================================= 2 . 10420.8 |=============================================================== 3 . 10853.5 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5730.72 |=============================================================== 2 . 5954.52 |================================================================= 3 . 6041.90 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 8.10435 |============================================================ 2 . 8.09766 |============================================================ 3 . 8.85443 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 10641.5 |================================================================ 2 . 10647.0 |================================================================ 3 . 10925.1 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 5907.30 |================================================================= 2 . 5822.13 |================================================================ 3 . 5981.80 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 7.32951 |================================================================== 2 . 7.33567 |================================================================== 3 . 7.23631 |================================================================= Opus Codec Encoding 1.3.1 WAV To Opus Encode Seconds < Lower Is Better 1 . 9.132 |==================================================================== 2 . 9.133 |==================================================================== 3 . 9.113 |==================================================================== simdjson 0.7.1 Throughput Test: Kostya GB/s > Higher Is Better 1 . 0.60 |===================================================================== 2 . 0.60 |===================================================================== 3 . 0.60 |===================================================================== simdjson 0.7.1 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.4 |====================================================================== 2 . 0.4 |====================================================================== 3 . 0.4 |====================================================================== simdjson 0.7.1 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 0.66 |===================================================================== 2 . 0.66 |===================================================================== 3 . 0.66 |===================================================================== simdjson 0.7.1 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 0.68 |===================================================================== 2 . 0.68 |===================================================================== 3 . 0.68 |===================================================================== SQLite Speedtest 3.30 Timed Time - Size 1,000 Seconds < Lower Is Better 1 . 80.19 |=================================================================== 2 . 81.52 |==================================================================== 3 . 80.10 |=================================================================== Timed Eigen Compilation 3.3.9 Time To Compile Seconds < Lower Is Better 1 . 96.66 |==================================================================== 2 . 97.29 |==================================================================== 3 . 97.30 |==================================================================== Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better 1 . 145.94 |=================================================================== 2 . 146.30 |=================================================================== 3 . 146.98 |=================================================================== Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 137.77 |=================================================================== 2 . 137.94 |=================================================================== 3 . 137.90 |=================================================================== VKMark 2020-05-21 Resolution: 1920 x 1080 VKMark Score > Higher Is Better 1 . 292 |====================================================================== 2 . 292 |====================================================================== 3 . 290 |====================================================================== WavPack Audio Encoding 5.3 WAV To WavPack Seconds < Lower Is Better 1 . 15.55 |==================================================================== 2 . 15.54 |==================================================================== 3 . 15.56 |====================================================================