icelake march
Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403273-NE-ICELAKEMA80&grs.
JPEG-XL libjxl
Input: PNG - Quality: 80
PyTorch
Device: CPU - Batch Size: 1 - Model: ResNet-152
PyTorch
Device: CPU - Batch Size: 1 - Model: ResNet-50
WavPack Audio Encoding
WAV To WavPack
RocksDB
Test: Sequential Fill
OpenVINO
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
TensorFlow
Device: CPU - Batch Size: 1 - Model: ResNet-50
RocksDB
Test: Overwrite
oneDNN
Harness: Deconvolution Batch shapes_1d - Engine: CPU
Chaos Group V-RAY
Mode: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
JPEG-XL libjxl
Input: PNG - Quality: 90
TensorFlow
Device: CPU - Batch Size: 16 - Model: GoogLeNet
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
OpenVINO
Model: Face Detection Retail FP16 - Device: CPU
RocksDB
Test: Read While Writing
RocksDB
Test: Random Read
OpenVINO
Model: Face Detection Retail FP16 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16-INT8 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
JPEG-XL libjxl
Input: JPEG - Quality: 90
JPEG-XL libjxl
Input: JPEG - Quality: 80
oneDNN
Harness: Convolution Batch Shapes Auto - Engine: CPU
TensorFlow
Device: CPU - Batch Size: 32 - Model: AlexNet
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
TensorFlow
Device: CPU - Batch Size: 64 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 32 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 16 - Model: ResNet-50
RocksDB
Test: Update Random
OpenVINO
Model: Person Re-Identification Retail FP16 - Device: CPU
OpenVINO
Model: Person Re-Identification Retail FP16 - Device: CPU
PyTorch
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
Stockfish
Chess Benchmark
OpenVINO
Model: Handwritten English Recognition FP16 - Device: CPU
oneDNN
Harness: Recurrent Neural Network Training - Engine: CPU
OpenVINO
Model: Handwritten English Recognition FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
TensorFlow
Device: CPU - Batch Size: 64 - Model: GoogLeNet
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
TensorFlow
Device: CPU - Batch Size: 64 - Model: ResNet-50
Blender
Blend File: BMW27 - Compute: CPU-Only
TensorFlow
Device: CPU - Batch Size: 16 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 32 - Model: ResNet-50
JPEG-XL libjxl
Input: PNG - Quality: 100
JPEG-XL Decoding libjxl
CPU Threads: All
Blender
Blend File: Pabellon Barcelona - Compute: CPU-Only
PyTorch
Device: CPU - Batch Size: 32 - Model: ResNet-152
RocksDB
Test: Random Fill
PyTorch
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
OpenVINO
Model: Person Detection FP32 - Device: CPU
Blender
Blend File: Fishy Cat - Compute: CPU-Only
OpenVINO
Model: Person Detection FP32 - Device: CPU
PyTorch
Device: CPU - Batch Size: 64 - Model: ResNet-152
JPEG-XL libjxl
Input: JPEG - Quality: 100
TensorFlow
Device: CPU - Batch Size: 1 - Model: GoogLeNet
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
Primesieve
Length: 1e12
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
PyTorch
Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l
PyTorch
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
PyTorch
Device: CPU - Batch Size: 16 - Model: ResNet-152
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 4K
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
oneDNN
Harness: IP Shapes 1D - Engine: CPU
RocksDB
Test: Read Random Write Random
OpenVINO
Model: Road Segmentation ADAS FP16 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16 - Device: CPU
Blender
Blend File: Junkshop - Compute: CPU-Only
PyTorch
Device: CPU - Batch Size: 16 - Model: ResNet-50
TensorFlow
Device: CPU - Batch Size: 1 - Model: AlexNet
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
PyTorch
Device: CPU - Batch Size: 64 - Model: ResNet-50
RocksDB
Test: Random Fill Sync
Parallel BZIP2 Compression
FreeBSD-13.0-RELEASE-amd64-memstick.img Compression
Google Draco
Model: Lion
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
oneDNN
Harness: Recurrent Neural Network Inference - Engine: CPU
JPEG-XL Decoding libjxl
CPU Threads: 1
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
Google Draco
Model: Church Facade
oneDNN
Harness: IP Shapes 3D - Engine: CPU
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
Timed Mesa Compilation
Time To Compile
oneDNN
Harness: Deconvolution Batch shapes_3d - Engine: CPU
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
Timed Linux Kernel Compilation
Build: defconfig
PyTorch
Device: CPU - Batch Size: 32 - Model: ResNet-50
Phoronix Test Suite v10.8.5