Core i5 10600K 2021
Intel Core i5-10600K testing with a ASUS PRIME Z490M-PLUS (1001 BIOS) and ASUS Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2101018-HA-COREI510692&sor&grs.
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
CLOMP
Static OMP Speedup
VkResample
Upscale: 2x - Precision: Double
VkResample
Upscale: 2x - Precision: Single
NCNN
Target: CPU - Model: regnety_400m
Build2
Time To Compile
NCNN
Target: CPU-v3-v3 - Model: mobilenet-v3
VKMark
Resolution: 3840 x 2160
NCNN
Target: CPU-v2-v2 - Model: mobilenet-v2
Cryptsetup
AES-XTS 256b Encryption
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
Cryptsetup
AES-XTS 256b Decryption
NCNN
Target: CPU - Model: yolov4-tiny
NCNN
Target: CPU - Model: blazeface
NCNN
Target: CPU - Model: alexnet
Cryptsetup
AES-XTS 512b Decryption
NCNN
Target: CPU - Model: squeezenet_ssd
NCNN
Target: Vulkan GPU - Model: mnasnet
NCNN
Target: CPU - Model: mnasnet
NCNN
Target: CPU - Model: mobilenet
NCNN
Target: CPU - Model: shufflenet-v2
NCNN
Target: CPU - Model: efficientnet-b0
Unpacking Firefox
Extracting: firefox-84.0.source.tar.xz
Cryptsetup
AES-XTS 512b Encryption
VKMark
Resolution: 1920 x 1200
NCNN
Target: Vulkan GPU - Model: regnety_400m
NCNN
Target: Vulkan GPU - Model: efficientnet-b0
NCNN
Target: Vulkan GPU - Model: shufflenet-v2
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
VKMark
Resolution: 2560 x 1440
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
NCNN
Target: Vulkan GPU - Model: mobilenet
NCNN
Target: Vulkan GPU - Model: blazeface
NCNN
Target: CPU - Model: vgg16
Timed Eigen Compilation
Time To Compile
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
NCNN
Target: CPU - Model: googlenet
NCNN
Target: Vulkan GPU - Model: resnet18
NCNN
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
Cryptsetup
Serpent-XTS 256b Encryption
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
NCNN
Target: Vulkan GPU - Model: googlenet
NCNN
Target: CPU - Model: resnet18
Monkey Audio Encoding
WAV To APE
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
NCNN
Target: CPU - Model: resnet50
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
NCNN
Target: Vulkan GPU - Model: alexnet
Cryptsetup
Twofish-XTS 256b Encryption
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
Cryptsetup
PBKDF2-sha512
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
Cryptsetup
Serpent-XTS 512b Encryption
Cryptsetup
Serpent-XTS 256b Decryption
Timed FFmpeg Compilation
Time To Compile
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
Opus Codec Encoding
WAV To Opus Encode
VKMark
Resolution: 1920 x 1080
NCNN
Target: Vulkan GPU - Model: yolov4-tiny
Cryptsetup
Twofish-XTS 512b Encryption
Cryptsetup
Serpent-XTS 512b Decryption
WavPack Audio Encoding
WAV To WavPack
NCNN
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
Cryptsetup
Twofish-XTS 512b Decryption
Cryptsetup
Twofish-XTS 256b Decryption
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
NCNN
Target: Vulkan GPU - Model: resnet50
NCNN
Target: Vulkan GPU - Model: squeezenet_ssd
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
Cryptsetup
PBKDF2-whirlpool
NCNN
Target: Vulkan GPU - Model: vgg16
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
Phoronix Test Suite v10.8.4