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.

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
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March 26
  4 Hours, 59 Minutes
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March 27
  4 Hours, 48 Minutes
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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","b" Processor,,Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads),Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads) Motherboard,,Dell 06CDVY (1.0.9 BIOS),Dell 06CDVY (1.0.9 BIOS) Chipset,,Intel Ice Lake-LP DRAM,Intel Ice Lake-LP DRAM Memory,,16GB,16GB Disk,,Toshiba KBG40ZPZ512G NVMe 512GB + 2 x 0GB MassStorageClass,Toshiba KBG40ZPZ512G NVMe 512GB + 2 x 0GB MassStorageClass Graphics,,Intel Iris Plus ICL GT2 16GB (1100MHz),Intel Iris Plus ICL GT2 16GB (1100MHz) Audio,,Realtek ALC289,Realtek ALC289 Network,,Intel Ice Lake-LP PCH CNVi WiFi,Intel Ice Lake-LP PCH CNVi WiFi OS,,Ubuntu 23.10,Ubuntu 23.10 Kernel,,6.7.0-060700rc5-generic (x86_64),6.7.0-060700rc5-generic (x86_64) Desktop,,GNOME Shell 45.1,GNOME Shell 45.1 Display Server,,X Server + Wayland,X Server + Wayland OpenGL,,4.6 Mesa 24.0~git2312230600.551924~oibaf~m (git-551924a 2023-12-23 mantic-oibaf-ppa),4.6 Mesa 24.0~git2312230600.551924~oibaf~m (git-551924a 2023-12-23 mantic-oibaf-ppa) Compiler,,GCC 13.2.0,GCC 13.2.0 File-System,,ext4,ext4 Screen Resolution,,1920x1200,1920x1200 ,,"a","b" "JPEG-XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,8.278,11.053 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,8.45,6.48 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,20.99,16.72 "WavPack Audio Encoding - WAV To WavPack (sec)",LIB,17.657,14.432 "RocksDB - Test: Sequential Fill (Op/s)",HIB,813335,940711 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,47.36,54.53 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,84.34,73.26 "TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,5.35,6.03 "RocksDB - Test: Overwrite (Op/s)",HIB,487116,541161 "oneDNN - Harness: Deconvolution Batch shapes_1d - Engine: CPU (ms)",LIB,18.832,16.9829 "Chaos Group V-RAY - Mode: CPU (vsamples)",HIB,3535,3899 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,43.9,39.97 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,90.92,99.85 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,7.26,7.94 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,548.85,502.55 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,36.88,40.23 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,108.37,99.37 "JPEG-XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,7.543,8.222 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,19.69,21.44 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,28.85,31.373 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,23.86,22.01 "RocksDB - Test: Read While Writing (Op/s)",HIB,500210,542153 "RocksDB - Test: Random Read (Op/s)",HIB,9192128,9961527 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,167.03,181 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,10.38,9.59 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,383.05,414.42 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,460.93,426.3 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,8.66,9.36 "JPEG-XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,7.662,8.256 "JPEG-XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,8.048,8.662 "oneDNN - Harness: Convolution Batch Shapes Auto - Engine: CPU (ms)",LIB,13.7106,12.755 "TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,42.93,46.1 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,16.82,15.67 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,236.71,253.97 "TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,45.59,48.86 "TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,20.09,21.52 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,7.28,7.79 "RocksDB - Test: Update Random (Op/s)",HIB,186334,199263 "OpenVINO - Model: Person Re-Identification Retail FP16 - Device: CPU (FPS)",HIB,98.25,105.03 "OpenVINO - Model: Person Re-Identification Retail FP16 - Device: CPU (ms)",LIB,40.64,38.02 "PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.43,4.73 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,4463.62,4765.04 "Stockfish - Chess Benchmark (Nodes/s)",HIB,2762544,2945032 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,123.07,115.5 "oneDNN - Harness: Recurrent Neural Network Training - Engine: CPU (ms)",LIB,12553.3,11783.6 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,32.47,34.59 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,1779.08,1894.37 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,0.63,0.67 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,6365.09,5987.53 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,2.2,2.07 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,63.77,67.76 "OpenVINO - Model: Noise Suppression Poconet-Like FP16 - Device: CPU (ms)",LIB,34.26,32.26 "TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,20.37,21.63 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.86,0.81 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,62.62,58.98 "OpenVINO - Model: Noise Suppression Poconet-Like FP16 - Device: CPU (FPS)",HIB,116.52,123.67 "TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,7.5,7.96 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,671.9,633.72 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,39.04,41.38 "TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,7.44,7.87 "JPEG-XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,2.997,3.169 "JPEG-XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,123.512,130.443 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,2207.35,2092.75 "PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-152 (batches/sec)",HIB,3.37,3.55 "RocksDB - Test: Random Fill (Op/s)",HIB,505433,532197 "PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,2.46,2.59 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,7.1,7.47 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,848.45,806.43 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,562.29,535.1 "PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-152 (batches/sec)",HIB,3.39,3.56 "JPEG-XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,2.981,3.13 "TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,22.17,23.26 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,77.47,73.91 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,51.59,54.06 "Primesieve - Length: 1e12 (sec)",LIB,88.592,84.583 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,3.643,3.806 "PyTorch - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l (batches/sec)",HIB,2.47,2.58 "PyTorch - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l (batches/sec)",HIB,2.48,2.59 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,2.37,2.47 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,3.45,3.59 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,25.118,26.134 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,132.9,138.11 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,30.02,28.89 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,1675.08,1614.49 "oneDNN - Harness: IP Shapes 1D - Engine: CPU (ms)",LIB,7.08037,6.82639 "RocksDB - Test: Read Random Write Random (Op/s)",HIB,504091,522145 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,26.34,27.27 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,151.61,146.48 "Blender - Blend File: Junkshop - Compute: CPU-Only (sec)",LIB,921.09,892.47 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,8.92,8.66 "TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,11.23,11.56 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,0.928,0.952 "PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-50 (batches/sec)",HIB,8.54,8.74 "RocksDB - Test: Random Fill Sync (Op/s)",HIB,1719,1683 "Parallel BZIP2 Compression - FreeBSD-13.0-RELEASE-amd64-memstick.img Compression (sec)",LIB,28.581235,28.096278 "Google Draco - Model: Lion (ms)",LIB,5559,5491 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,24.902,24.624 "oneDNN - Harness: Recurrent Neural Network Inference - Engine: CPU (ms)",LIB,6399.73,6341.9 "JPEG-XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,57.584,58.041 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,240.46,238.626 "Google Draco - Model: Church Facade (ms)",LIB,8421,8361 "oneDNN - Harness: IP Shapes 3D - Engine: CPU (ms)",LIB,5.80745,5.83135 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,184.734,184.085 "Timed Mesa Compilation - Time To Compile (sec)",LIB,143.674,143.249 "oneDNN - Harness: Deconvolution Batch shapes_3d - Engine: CPU (ms)",LIB,13.4544,13.4885 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,7.551,7.569 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,496.16,497.181 "PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-50 (batches/sec)",HIB,8.69,8.68