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
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Limit displaying results to tests within:

Timed Code Compilation 2 Tests
C/C++ Compiler Tests 2 Tests
CPU Massive 9 Tests
Creator Workloads 9 Tests
Encoding 2 Tests
Game Development 2 Tests
HPC - High Performance Computing 4 Tests
Imaging 2 Tests
Machine Learning 4 Tests
Multi-Core 10 Tests
NVIDIA GPU Compute 2 Tests
Intel oneAPI 2 Tests
Programmer / Developer System Benchmarks 2 Tests
Python Tests 4 Tests
Renderers 2 Tests
Server CPU Tests 5 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
a
March 26
  4 Hours, 59 Minutes
b
March 27
  4 Hours, 48 Minutes
Invert Hiding All Results Option
  4 Hours, 54 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):

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 |=================================================================== 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 |=====================================================================