10600K pre RKL
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/2103183-IB-10600KPRE35&grs&rdt&rro.
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
Xcompact3d Incompact3d
Input: input.i3d 129 Cells Per Direction
Mobile Neural Network
Model: SqueezeNetV1.0
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
Mobile Neural Network
Model: mobilenet-v1-1.0
Xcompact3d Incompact3d
Input: input.i3d 193 Cells Per Direction
Sysbench
Test: RAM / Memory
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
AOM AV1
Encoder Mode: Speed 6 Realtime
ASTC Encoder
Preset: Exhaustive
SVT-HEVC
Tuning: 7 - Input: Bosphorus 1080p
Mobile Neural Network
Model: inception-v3
Basis Universal
Settings: ETC1S
Mobile Neural Network
Model: MobileNetV2_224
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
AOM AV1
Encoder Mode: Speed 8 Realtime
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
Mobile Neural Network
Model: resnet-v2-50
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
simdjson
Throughput Test: Kostya
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
SVT-HEVC
Tuning: 10 - Input: Bosphorus 1080p
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ASTC Encoder
Preset: Thorough
SVT-VP9
Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 6 Two-Pass
simdjson
Throughput Test: PartialTweets
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
Timed Mesa Compilation
Time To Compile
SVT-VP9
Tuning: VMAF Optimized - Input: Bosphorus 1080p
ASTC Encoder
Preset: Medium
SVT-HEVC
Tuning: 1 - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 4 Two-Pass
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
Timed Node.js Compilation
Time To Compile
SVT-VP9
Tuning: Visual Quality Optimized - Input: Bosphorus 1080p
Basis Universal
Settings: UASTC Level 0
Basis Universal
Settings: UASTC Level 2
Basis Universal
Settings: UASTC Level 3
Sysbench
Test: CPU
AOM AV1
Encoder Mode: Speed 0 Two-Pass
simdjson
Throughput Test: DistinctUserID
simdjson
Throughput Test: LargeRandom
Phoronix Test Suite v10.8.5