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. 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 |=================================================================== JPEG-XL libjxl 0.10.1 Input: PNG - Quality: 90 MP/s > Higher Is Better a . 7.543 |============================================================== b . 8.222 |==================================================================== JPEG-XL libjxl 0.10.1 Input: JPEG - Quality: 80 MP/s > Higher Is Better a . 8.048 |=============================================================== b . 8.662 |==================================================================== 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: PNG - Quality: 100 MP/s > Higher Is Better a . 2.997 |================================================================ b . 3.169 |==================================================================== JPEG-XL libjxl 0.10.1 Input: JPEG - Quality: 100 MP/s > Higher Is Better a . 2.981 |================================================================= b . 3.130 |==================================================================== JPEG-XL Decoding libjxl 0.10.1 CPU Threads: 1 MP/s > Higher Is Better a . 57.58 |=================================================================== b . 58.04 |==================================================================== JPEG-XL Decoding libjxl 0.10.1 CPU Threads: All MP/s > Higher Is Better a . 123.51 |=============================================================== b . 130.44 |=================================================================== SVT-AV1 2.0 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 0.928 |================================================================== b . 0.952 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 7.551 |==================================================================== b . 7.569 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 24.90 |==================================================================== b . 24.62 |=================================================================== SVT-AV1 2.0 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 25.12 |================================================================= b . 26.13 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 3.643 |================================================================= b . 3.806 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 28.85 |=============================================================== b . 31.37 |==================================================================== SVT-AV1 2.0 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 184.73 |=================================================================== b . 184.09 |=================================================================== SVT-AV1 2.0 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 240.46 |=================================================================== b . 238.63 |================================================================== Stockfish 16.1 Chess Benchmark Nodes Per Second > Higher Is Better a . 2762544 |============================================================== b . 2945032 |================================================================== Timed Linux Kernel Compilation 6.8 Build: defconfig Seconds < Lower Is Better a . 496.16 |=================================================================== b . 497.18 |=================================================================== Timed Mesa Compilation 24.0 Time To Compile Seconds < Lower Is Better a . 143.67 |=================================================================== b . 143.25 |=================================================================== Parallel BZIP2 Compression 1.1.13 FreeBSD-13.0-RELEASE-amd64-memstick.img Compression Seconds < Lower Is Better a . 28.58 |==================================================================== b . 28.10 |=================================================================== Primesieve 12.1 Length: 1e12 Seconds < Lower Is Better a . 88.59 |==================================================================== b . 84.58 |================================================================= oneDNN 3.4 Harness: IP Shapes 1D - Engine: CPU ms < Lower Is Better a . 7.08037 |================================================================== b . 6.82639 |================================================================ oneDNN 3.4 Harness: IP Shapes 3D - Engine: CPU ms < Lower Is Better a . 5.80745 |================================================================== b . 5.83135 |================================================================== oneDNN 3.4 Harness: Convolution Batch Shapes Auto - Engine: CPU ms < Lower Is Better a . 13.71 |==================================================================== b . 12.76 |=============================================================== oneDNN 3.4 Harness: Deconvolution Batch shapes_1d - Engine: CPU ms < Lower Is Better a . 18.83 |==================================================================== b . 16.98 |============================================================= oneDNN 3.4 Harness: Deconvolution Batch shapes_3d - Engine: CPU ms < Lower Is Better a . 13.45 |==================================================================== b . 13.49 |==================================================================== oneDNN 3.4 Harness: Recurrent Neural Network Training - Engine: CPU ms < Lower Is Better a . 12553.3 |================================================================== b . 11783.6 |============================================================== oneDNN 3.4 Harness: Recurrent Neural Network Inference - Engine: CPU ms < Lower Is Better a . 6399.73 |================================================================== b . 6341.90 |================================================================= Google Draco 1.5.6 Model: Lion ms < Lower Is Better a . 5559 |===================================================================== b . 5491 |==================================================================== Google Draco 1.5.6 Model: Church Facade ms < Lower Is Better a . 8421 |===================================================================== b . 8361 |===================================================================== Blender 4.1 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 671.90 |=================================================================== b . 633.72 |=============================================================== Blender 4.1 Blend File: Junkshop - Compute: CPU-Only Seconds < Lower Is Better a . 921.09 |=================================================================== b . 892.47 |================================================================= Blender 4.1 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 848.45 |=================================================================== b . 806.43 |================================================================ Blender 4.1 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 2207.35 |================================================================== b . 2092.75 |=============================================================== 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: 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: Person Detection FP32 - Device: CPU FPS > Higher Is Better a . 7.10 |================================================================== b . 7.47 |===================================================================== OpenVINO 2024.0 Model: Person Detection FP32 - Device: CPU ms < Lower Is Better a . 562.29 |=================================================================== b . 535.10 |================================================================ OpenVINO 2024.0 Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better a . 51.59 |================================================================= b . 54.06 |==================================================================== OpenVINO 2024.0 Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better a . 77.47 |==================================================================== b . 73.91 |================================================================= OpenVINO 2024.0 Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 2.37 |================================================================== b . 2.47 |===================================================================== OpenVINO 2024.0 Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 1675.08 |================================================================== b . 1614.49 |================================================================ 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 - Device: CPU ms < Lower Is Better a . 23.86 |==================================================================== b . 22.01 |=============================================================== 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 |================================================================= 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: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better a . 63.77 |================================================================ b . 67.76 |==================================================================== OpenVINO 2024.0 Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better a . 62.62 |==================================================================== b . 58.98 |================================================================ 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: Face Detection Retail FP16-INT8 - Device: CPU ms < Lower Is Better a . 10.38 |==================================================================== b . 9.59 |=============================================================== 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 |=========================================================== OpenVINO 2024.0 Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better a . 8.66 |================================================================ b . 9.36 |===================================================================== 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: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 236.71 |============================================================== b . 253.97 |=================================================================== 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: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better a . 90.92 |============================================================== b . 99.85 |==================================================================== 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: Noise Suppression Poconet-Like FP16 - Device: CPU FPS > Higher Is Better a . 116.52 |=============================================================== b . 123.67 |=================================================================== OpenVINO 2024.0 Model: Noise Suppression Poconet-Like FP16 - Device: CPU ms < Lower Is Better a . 34.26 |==================================================================== b . 32.26 |================================================================ OpenVINO 2024.0 Model: Handwritten English Recognition FP16 - Device: CPU FPS > Higher Is Better a . 32.47 |================================================================ b . 34.59 |==================================================================== OpenVINO 2024.0 Model: Handwritten English Recognition FP16 - Device: CPU ms < Lower Is Better a . 123.07 |=================================================================== b . 115.50 |=============================================================== 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 |================================================================ 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: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better a . 2.20 |===================================================================== b . 2.07 |================================================================= 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 |============================================================= OpenVINO 2024.0 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better a . 4463.62 |============================================================== b . 4765.04 |================================================================== OpenVINO 2024.0 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better a . 0.86 |===================================================================== b . 0.81 |================================================================= RocksDB 9.0 Test: Overwrite Op/s > Higher Is Better a . 487116 |============================================================ b . 541161 |=================================================================== RocksDB 9.0 Test: Random Fill Op/s > Higher Is Better a . 505433 |================================================================ b . 532197 |=================================================================== RocksDB 9.0 Test: Random Read Op/s > Higher Is Better a . 9192128 |============================================================= b . 9961527 |================================================================== RocksDB 9.0 Test: Update Random Op/s > Higher Is Better a . 186334 |=============================================================== b . 199263 |=================================================================== RocksDB 9.0 Test: Sequential Fill Op/s > Higher Is Better a . 813335 |========================================================== b . 940711 |=================================================================== RocksDB 9.0 Test: Random Fill Sync Op/s > Higher Is Better a . 1719 |===================================================================== b . 1683 |==================================================================== RocksDB 9.0 Test: Read While Writing Op/s > Higher Is Better a . 500210 |============================================================== b . 542153 |=================================================================== RocksDB 9.0 Test: Read Random Write Random Op/s > Higher Is Better a . 504091 |================================================================= b . 522145 |=================================================================== WavPack Audio Encoding 5.7 WAV To WavPack Seconds < Lower Is Better a . 17.66 |==================================================================== b . 14.43 |======================================================== Chaos Group V-RAY 6.0 Mode: CPU vsamples > Higher Is Better a . 3535 |=============================================================== b . 3899 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 20.99 |==================================================================== b . 16.72 |====================================================== 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: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 8.92 |===================================================================== b . 8.66 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 8.69 |===================================================================== b . 8.68 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better a . 8.54 |=================================================================== b . 8.74 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 3.45 |================================================================== b . 3.59 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better a . 3.37 |================================================================== b . 3.55 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better a . 3.39 |================================================================== b . 3.56 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 4.43 |================================================================= b . 4.73 |===================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 2.46 |================================================================== b . 2.59 |===================================================================== 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 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 11.23 |================================================================== b . 11.56 |==================================================================== 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: AlexNet images/sec > Higher Is Better a . 42.93 |=============================================================== b . 46.10 |==================================================================== 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: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 22.17 |================================================================= b . 23.26 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 5.35 |============================================================= b . 6.03 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 19.69 |============================================================== b . 21.44 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 7.28 |================================================================ b . 7.79 |===================================================================== 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: 32 - Model: ResNet-50 images/sec > Higher Is Better a . 7.44 |================================================================= b . 7.87 |===================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet images/sec > Higher Is Better a . 20.37 |================================================================ b . 21.63 |==================================================================== TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 images/sec > Higher Is Better a . 7.50 |================================================================= b . 7.96 |=====================================================================