Tests for a future article. 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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2403278-NE-ICELAKEMA14
icelake march
Tests for a future article. 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.
a:
Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB + 2 x 0GB MassStorageClass, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi
OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 24.0~git2312230600.551924~oibaf~m (git-551924a 2023-12-23 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
b:
Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB + 2 x 0GB MassStorageClass, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi
OS: Ubuntu 23.10, Kernel: 6.7.0-060700rc5-generic (x86_64), Desktop: GNOME Shell 45.1, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 24.0~git2312230600.551924~oibaf~m (git-551924a 2023-12-23 mantic-oibaf-ppa), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
JPEG-XL libjxl 0.10.1
Input: PNG - Quality: 80
MP/s > Higher Is Better
a . 8.278 |==================================================
b . 11.053 |===================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
a . 8.45 |=====================================================================
b . 6.48 |=====================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
a . 20.99 |====================================================================
b . 16.72 |======================================================
WavPack Audio Encoding 5.7
WAV To WavPack
Seconds < Lower Is Better
a . 17.66 |====================================================================
b . 14.43 |========================================================
RocksDB 9.0
Test: Sequential Fill
Op/s > Higher Is Better
a . 813335 |==========================================================
b . 940711 |===================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 47.36 |===========================================================
b . 54.53 |====================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 84.34 |====================================================================
b . 73.26 |===========================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
images/sec > Higher Is Better
a . 5.35 |=============================================================
b . 6.03 |=====================================================================
RocksDB 9.0
Test: Overwrite
Op/s > Higher Is Better
a . 487116 |============================================================
b . 541161 |===================================================================
oneDNN 3.4
Harness: Deconvolution Batch shapes_1d - Engine: CPU
ms < Lower Is Better
a . 18.83 |====================================================================
b . 16.98 |=============================================================
Chaos Group V-RAY 6.0
Mode: CPU
vsamples > Higher Is Better
a . 3535 |===============================================================
b . 3899 |=====================================================================
OpenVINO 2024.0
Model: Person Vehicle Bike Detection FP16 - Device: CPU
ms < Lower Is Better
a . 43.90 |====================================================================
b . 39.97 |==============================================================
OpenVINO 2024.0
Model: Person Vehicle Bike Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 90.92 |==============================================================
b . 99.85 |====================================================================
OpenVINO 2024.0
Model: Person Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 7.26 |===============================================================
b . 7.94 |=====================================================================
OpenVINO 2024.0
Model: Person Detection FP16 - Device: CPU
ms < Lower Is Better
a . 548.85 |===================================================================
b . 502.55 |=============================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 36.88 |==============================================================
b . 40.23 |====================================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 108.37 |===================================================================
b . 99.37 |=============================================================
JPEG-XL libjxl 0.10.1
Input: PNG - Quality: 90
MP/s > Higher Is Better
a . 7.543 |==============================================================
b . 8.222 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
a . 19.69 |==============================================================
b . 21.44 |====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 28.85 |===============================================================
b . 31.37 |====================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16 - Device: CPU
ms < Lower Is Better
a . 23.86 |====================================================================
b . 22.01 |===============================================================
RocksDB 9.0
Test: Read While Writing
Op/s > Higher Is Better
a . 500210 |==============================================================
b . 542153 |===================================================================
RocksDB 9.0
Test: Random Read
Op/s > Higher Is Better
a . 9192128 |=============================================================
b . 9961527 |==================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16 - Device: CPU
FPS > Higher Is Better
a . 167.03 |==============================================================
b . 181.00 |===================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 10.38 |====================================================================
b . 9.59 |===============================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 383.05 |==============================================================
b . 414.42 |===================================================================
OpenVINO 2024.0
Model: Machine Translation EN To DE FP16 - Device: CPU
ms < Lower Is Better
a . 460.93 |===================================================================
b . 426.30 |==============================================================
OpenVINO 2024.0
Model: Machine Translation EN To DE FP16 - Device: CPU
FPS > Higher Is Better
a . 8.66 |================================================================
b . 9.36 |=====================================================================
JPEG-XL libjxl 0.10.1
Input: JPEG - Quality: 90
MP/s > Higher Is Better
a . 7.662 |===============================================================
b . 8.256 |====================================================================
JPEG-XL libjxl 0.10.1
Input: JPEG - Quality: 80
MP/s > Higher Is Better
a . 8.048 |===============================================================
b . 8.662 |====================================================================
oneDNN 3.4
Harness: Convolution Batch Shapes Auto - Engine: CPU
ms < Lower Is Better
a . 13.71 |====================================================================
b . 12.76 |===============================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: AlexNet
images/sec > Higher Is Better
a . 42.93 |===============================================================
b . 46.10 |====================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 16.82 |====================================================================
b . 15.67 |===============================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 236.71 |==============================================================
b . 253.97 |===================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: AlexNet
images/sec > Higher Is Better
a . 45.59 |===============================================================
b . 48.86 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: GoogLeNet
images/sec > Higher Is Better
a . 20.09 |===============================================================
b . 21.52 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
a . 7.28 |================================================================
b . 7.79 |=====================================================================
RocksDB 9.0
Test: Update Random
Op/s > Higher Is Better
a . 186334 |===============================================================
b . 199263 |===================================================================
OpenVINO 2024.0
Model: Person Re-Identification Retail FP16 - Device: CPU
FPS > Higher Is Better
a . 98.25 |===============================================================
b . 105.03 |===================================================================
OpenVINO 2024.0
Model: Person Re-Identification Retail FP16 - Device: CPU
ms < Lower Is Better
a . 40.64 |====================================================================
b . 38.02 |================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 4.43 |=================================================================
b . 4.73 |=====================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 4463.62 |==============================================================
b . 4765.04 |==================================================================
Stockfish 16.1
Chess Benchmark
Nodes Per Second > Higher Is Better
a . 2762544 |==============================================================
b . 2945032 |==================================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16 - Device: CPU
ms < Lower Is Better
a . 123.07 |===================================================================
b . 115.50 |===============================================================
oneDNN 3.4
Harness: Recurrent Neural Network Training - Engine: CPU
ms < Lower Is Better
a . 12553.3 |==================================================================
b . 11783.6 |==============================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16 - Device: CPU
FPS > Higher Is Better
a . 32.47 |================================================================
b . 34.59 |====================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
FPS > Higher Is Better
a . 1779.08 |==============================================================
b . 1894.37 |==================================================================
OpenVINO 2024.0
Model: Face Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 0.63 |=================================================================
b . 0.67 |=====================================================================
OpenVINO 2024.0
Model: Face Detection FP16 - Device: CPU
ms < Lower Is Better
a . 6365.09 |==================================================================
b . 5987.53 |==============================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
ms < Lower Is Better
a . 2.20 |=====================================================================
b . 2.07 |=================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 63.77 |================================================================
b . 67.76 |====================================================================
OpenVINO 2024.0
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
ms < Lower Is Better
a . 34.26 |====================================================================
b . 32.26 |================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: GoogLeNet
images/sec > Higher Is Better
a . 20.37 |================================================================
b . 21.63 |====================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 0.86 |=====================================================================
b . 0.81 |=================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16 - Device: CPU
ms < Lower Is Better
a . 62.62 |====================================================================
b . 58.98 |================================================================
OpenVINO 2024.0
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
FPS > Higher Is Better
a . 116.52 |===============================================================
b . 123.67 |===================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
images/sec > Higher Is Better
a . 7.50 |=================================================================
b . 7.96 |=====================================================================
Blender 4.1
Blend File: BMW27 - Compute: CPU-Only
Seconds < Lower Is Better
a . 671.90 |===================================================================
b . 633.72 |===============================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
a . 39.04 |================================================================
b . 41.38 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
images/sec > Higher Is Better
a . 7.44 |=================================================================
b . 7.87 |=====================================================================
JPEG-XL libjxl 0.10.1
Input: PNG - Quality: 100
MP/s > Higher Is Better
a . 2.997 |================================================================
b . 3.169 |====================================================================
JPEG-XL Decoding libjxl 0.10.1
CPU Threads: All
MP/s > Higher Is Better
a . 123.51 |===============================================================
b . 130.44 |===================================================================
Blender 4.1
Blend File: Pabellon Barcelona - Compute: CPU-Only
Seconds < Lower Is Better
a . 2207.35 |==================================================================
b . 2092.75 |===============================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
a . 3.37 |==================================================================
b . 3.55 |=====================================================================
RocksDB 9.0
Test: Random Fill
Op/s > Higher Is Better
a . 505433 |================================================================
b . 532197 |===================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 2.46 |==================================================================
b . 2.59 |=====================================================================
OpenVINO 2024.0
Model: Person Detection FP32 - Device: CPU
FPS > Higher Is Better
a . 7.10 |==================================================================
b . 7.47 |=====================================================================
Blender 4.1
Blend File: Fishy Cat - Compute: CPU-Only
Seconds < Lower Is Better
a . 848.45 |===================================================================
b . 806.43 |================================================================
OpenVINO 2024.0
Model: Person Detection FP32 - Device: CPU
ms < Lower Is Better
a . 562.29 |===================================================================
b . 535.10 |================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better
a . 3.39 |==================================================================
b . 3.56 |=====================================================================
JPEG-XL libjxl 0.10.1
Input: JPEG - Quality: 100
MP/s > Higher Is Better
a . 2.981 |=================================================================
b . 3.130 |====================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: GoogLeNet
images/sec > Higher Is Better
a . 22.17 |=================================================================
b . 23.26 |====================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16 - Device: CPU
ms < Lower Is Better
a . 77.47 |====================================================================
b . 73.91 |=================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 51.59 |=================================================================
b . 54.06 |====================================================================
Primesieve 12.1
Length: 1e12
Seconds < Lower Is Better
a . 88.59 |====================================================================
b . 84.58 |=================================================================
SVT-AV1 2.0
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 3.643 |=================================================================
b . 3.806 |====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 2.47 |==================================================================
b . 2.58 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 2.48 |==================================================================
b . 2.59 |=====================================================================
OpenVINO 2024.0
Model: Face Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 2.37 |==================================================================
b . 2.47 |=====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
a . 3.45 |==================================================================
b . 3.59 |=====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 13 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 25.12 |=================================================================
b . 26.13 |====================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 132.90 |================================================================
b . 138.11 |===================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 30.02 |====================================================================
b . 28.89 |=================================================================
OpenVINO 2024.0
Model: Face Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 1675.08 |==================================================================
b . 1614.49 |================================================================
oneDNN 3.4
Harness: IP Shapes 1D - Engine: CPU
ms < Lower Is Better
a . 7.08037 |==================================================================
b . 6.82639 |================================================================
RocksDB 9.0
Test: Read Random Write Random
Op/s > Higher Is Better
a . 504091 |=================================================================
b . 522145 |===================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16 - Device: CPU
FPS > Higher Is Better
a . 26.34 |==================================================================
b . 27.27 |====================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16 - Device: CPU
ms < Lower Is Better
a . 151.61 |===================================================================
b . 146.48 |=================================================================
Blender 4.1
Blend File: Junkshop - Compute: CPU-Only
Seconds < Lower Is Better
a . 921.09 |===================================================================
b . 892.47 |=================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
a . 8.92 |=====================================================================
b . 8.66 |===================================================================
TensorFlow 2.16.1
Device: CPU - Batch Size: 1 - Model: AlexNet
images/sec > Higher Is Better
a . 11.23 |==================================================================
b . 11.56 |====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 4 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 0.928 |==================================================================
b . 0.952 |====================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
a . 8.54 |===================================================================
b . 8.74 |=====================================================================
RocksDB 9.0
Test: Random Fill Sync
Op/s > Higher Is Better
a . 1719 |=====================================================================
b . 1683 |====================================================================
Parallel BZIP2 Compression 1.1.13
FreeBSD-13.0-RELEASE-amd64-memstick.img Compression
Seconds < Lower Is Better
a . 28.58 |====================================================================
b . 28.10 |===================================================================
Google Draco 1.5.6
Model: Lion
ms < Lower Is Better
a . 5559 |=====================================================================
b . 5491 |====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 12 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 24.90 |====================================================================
b . 24.62 |===================================================================
oneDNN 3.4
Harness: Recurrent Neural Network Inference - Engine: CPU
ms < Lower Is Better
a . 6399.73 |==================================================================
b . 6341.90 |=================================================================
JPEG-XL Decoding libjxl 0.10.1
CPU Threads: 1
MP/s > Higher Is Better
a . 57.58 |===================================================================
b . 58.04 |====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 240.46 |===================================================================
b . 238.63 |==================================================================
Google Draco 1.5.6
Model: Church Facade
ms < Lower Is Better
a . 8421 |=====================================================================
b . 8361 |=====================================================================
oneDNN 3.4
Harness: IP Shapes 3D - Engine: CPU
ms < Lower Is Better
a . 5.80745 |==================================================================
b . 5.83135 |==================================================================
SVT-AV1 2.0
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 184.73 |===================================================================
b . 184.09 |===================================================================
Timed Mesa Compilation 24.0
Time To Compile
Seconds < Lower Is Better
a . 143.67 |===================================================================
b . 143.25 |===================================================================
oneDNN 3.4
Harness: Deconvolution Batch shapes_3d - Engine: CPU
ms < Lower Is Better
a . 13.45 |====================================================================
b . 13.49 |====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 8 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 7.551 |====================================================================
b . 7.569 |====================================================================
Timed Linux Kernel Compilation 6.8
Build: defconfig
Seconds < Lower Is Better
a . 496.16 |===================================================================
b . 497.18 |===================================================================
PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better
a . 8.69 |=====================================================================
b . 8.68 |=====================================================================