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
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
CLOMP 1.2
Static OMP Speedup
Speedup > Higher Is Better
1 . 0.9 |=========================================================
2 . 1.1 |======================================================================
3 . 1.1 |======================================================================
Build2 0.13
Time To Compile
Seconds < Lower Is Better
1 . 388.39 |===================================================================
2 . 385.58 |==================================================================
3 . 388.95 |===================================================================
BRL-CAD 7.30.8
VGR Performance Metric
VGR Performance Metric > Higher Is Better
1 . 42373 |====================================================================
2 . 42365 |====================================================================
3 . 42169 |====================================================================
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 |===================================================================
NCNN 20201218
Target: Vulkan GPU - Model: regnety_400m
ms < Lower Is Better
1 . 20.70 |===================================================================
2 . 20.75 |====================================================================
3 . 20.88 |====================================================================
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: yolov4-tiny
ms < Lower Is Better
1 . 51.83 |==================================================================
2 . 53.05 |===================================================================
3 . 53.45 |====================================================================
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: alexnet
ms < Lower Is Better
1 . 25.09 |===================================================================
2 . 25.62 |====================================================================
3 . 25.11 |===================================================================
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: vgg16
ms < Lower Is Better
1 . 126.48 |==================================================================
2 . 128.34 |===================================================================
3 . 127.97 |===================================================================
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: blazeface
ms < Lower Is Better
1 . 3.25 |=====================================================================
2 . 3.18 |====================================================================
3 . 3.24 |=====================================================================
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: mnasnet
ms < Lower Is Better
1 . 8.53 |=====================================================================
2 . 8.41 |====================================================================
3 . 8.43 |====================================================================
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-v3-v3 - Model: mobilenet-v3
ms < Lower Is Better
1 . 8.77 |====================================================================
2 . 8.72 |====================================================================
3 . 8.84 |=====================================================================
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 - Model: mobilenet
ms < Lower Is Better
1 . 39.24 |===================================================================
2 . 39.55 |====================================================================
3 . 39.64 |====================================================================
NCNN 20201218
Target: CPU - Model: regnety_400m
ms < Lower Is Better
1 . 20.69 |===================================================================
2 . 20.55 |===================================================================
3 . 20.90 |====================================================================
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: yolov4-tiny
ms < Lower Is Better
1 . 51.58 |=================================================================
2 . 52.98 |==================================================================
3 . 54.23 |====================================================================
NCNN 20201218
Target: CPU - Model: resnet50
ms < Lower Is Better
1 . 61.85 |==================================================================
2 . 63.27 |===================================================================
3 . 64.10 |====================================================================
NCNN 20201218
Target: CPU - Model: alexnet
ms < Lower Is Better
1 . 25.10 |====================================================================
2 . 25.16 |====================================================================
3 . 25.17 |====================================================================
NCNN 20201218
Target: CPU - Model: resnet18
ms < Lower Is Better
1 . 30.48 |==================================================================
2 . 31.42 |====================================================================
3 . 30.75 |===================================================================
NCNN 20201218
Target: CPU - Model: vgg16
ms < Lower Is Better
1 . 127.46 |===================================================================
2 . 127.55 |===================================================================
3 . 128.02 |===================================================================
NCNN 20201218
Target: CPU - Model: googlenet
ms < Lower Is Better
1 . 29.65 |==================================================================
2 . 30.43 |====================================================================
3 . 30.19 |===================================================================
NCNN 20201218
Target: CPU - Model: blazeface
ms < Lower Is Better
1 . 3.29 |=====================================================================
2 . 3.17 |==================================================================
3 . 3.28 |=====================================================================
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: mnasnet
ms < Lower Is Better
1 . 8.37 |===================================================================
2 . 8.42 |===================================================================
3 . 8.65 |=====================================================================
NCNN 20201218
Target: CPU - Model: shufflenet-v2
ms < Lower Is Better
1 . 11.41 |====================================================================
2 . 11.42 |====================================================================
3 . 11.44 |====================================================================
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-v2-v2 - Model: mobilenet-v2
ms < Lower Is Better
1 . 10.42 |================================================================
2 . 10.66 |==================================================================
3 . 11.04 |====================================================================
NCNN 20201218
Target: CPU - Model: mobilenet
ms < Lower Is Better
1 . 39.30 |===================================================================
2 . 39.29 |===================================================================
3 . 39.77 |====================================================================
VKMark 2020-05-21
Resolution: 1920 x 1080
VKMark Score > Higher Is Better
1 . 292 |======================================================================
2 . 292 |======================================================================
3 . 290 |======================================================================
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 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 Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 10419.2 |================================================================
2 . 10472.4 |=================================================================
3 . 10683.5 |==================================================================
Timed Eigen Compilation 3.3.9
Time To Compile
Seconds < Lower Is Better
1 . 96.66 |====================================================================
2 . 97.29 |====================================================================
3 . 97.30 |====================================================================
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: 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 Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
1 . 5907.30 |=================================================================
2 . 5822.13 |================================================================
3 . 5981.80 |==================================================================
Node.js V8 Web Tooling Benchmark
runs/s > Higher Is Better
1 . 9.30 |=====================================================================
2 . 9.29 |=====================================================================
3 . 9.24 |=====================================================================
SQLite Speedtest 3.30
Timed Time - Size 1,000
Seconds < Lower Is Better
1 . 80.19 |===================================================================
2 . 81.52 |====================================================================
3 . 80.10 |===================================================================
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: DistinctUserID
GB/s > Higher Is Better
1 . 0.68 |=====================================================================
2 . 0.68 |=====================================================================
3 . 0.68 |=====================================================================
simdjson 0.7.1
Throughput Test: PartialTweets
GB/s > Higher Is Better
1 . 0.66 |=====================================================================
2 . 0.66 |=====================================================================
3 . 0.66 |=====================================================================
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 |===================================================================
Coremark 1.0
CoreMark Size 666 - Iterations Per Second
Iterations/Sec > Higher Is Better
1 . 144430.97 |================================================================
2 . 144054.76 |================================================================
3 . 144381.89 |================================================================
WavPack Audio Encoding 5.3
WAV To WavPack
Seconds < Lower Is Better
1 . 15.55 |====================================================================
2 . 15.54 |====================================================================
3 . 15.56 |====================================================================
Monkey Audio Encoding 3.99.6
WAV To APE
Seconds < Lower Is Better
1 . 14.06 |====================================================================
2 . 13.87 |===================================================================
3 . 13.95 |===================================================================
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: 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: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
1 . 15.91 |=========================================================
2 . 15.65 |========================================================
3 . 18.89 |====================================================================
Opus Codec Encoding 1.3.1
WAV To Opus Encode
Seconds < Lower Is Better
1 . 9.132 |====================================================================
2 . 9.133 |====================================================================
3 . 9.113 |====================================================================
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 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 5.97793 |==================================================================
2 . 5.94146 |=================================================================
3 . 5.99872 |==================================================================
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 |=================================================================
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: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 31.03 |====================================================================
2 . 30.93 |====================================================================
3 . 30.95 |====================================================================
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_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
1 . 12.96 |====================================================================
2 . 12.95 |====================================================================
3 . 12.90 |====================================================================
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 |====================================================================