icelake 31 march

Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 22.04 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 2304013-NE-ICELAKE3183
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a
March 31 2023
  4 Hours, 29 Minutes
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April 01 2023
  1 Hour, 13 Minutes
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April 01 2023
  1 Hour, 14 Minutes
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April 01 2023
  1 Hour, 14 Minutes
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icelake 31 march Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 22.04 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, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi OS: Ubuntu 22.04, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, 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, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi OS: Ubuntu 22.04, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1200 c: 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, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi OS: Ubuntu 22.04, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1200 d: 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, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi OS: Ubuntu 22.04, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 42.2, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 22.0.1, OpenCL: OpenCL 3.0, Vulkan: 1.3.204, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1920x1200 Blender 3.5 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 667.82 |=================================================================== b . 607.66 |============================================================= c . 610.25 |============================================================= d . 629.05 |=============================================================== Blender 3.5 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 853.93 |=================================================================== b . 787.19 |============================================================== c . 800.37 |=============================================================== d . 790.54 |============================================================== Blender 3.5 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 2258.20 |================================================================== b . 2127.09 |============================================================== c . 2170.73 |=============================================================== d . 2102.53 |============================================================= oneDNN 3.1 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 9.82185 |============================================================== b . 10.34370 |================================================================= c . 10.12130 |================================================================ d . 9.84325 |============================================================== oneDNN 3.1 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 6.81592 |================================================================== b . 6.66296 |================================================================= c . 6.65945 |================================================================ d . 6.68831 |================================================================= oneDNN 3.1 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3.56346 |================================================================== b . 2.16527 |======================================== c . 2.11974 |======================================= d . 2.08567 |======================================= oneDNN 3.1 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 4.22282 |================================================================== b . 2.65931 |========================================== c . 2.64073 |========================================= d . 2.81508 |============================================ oneDNN 3.1 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 35.56 |==================================================================== b . 24.39 |=============================================== c . 24.10 |============================================== d . 24.68 |=============================================== oneDNN 3.1 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 11.72450 |================================================================= b . 7.59195 |========================================== c . 7.62148 |========================================== d . 8.35993 |============================================== oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 17.07 |==================================================================== b . 12.72 |=================================================== c . 12.92 |=================================================== d . 12.99 |==================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 23.49 |==================================================================== b . 15.23 |============================================ c . 15.31 |============================================ d . 20.21 |=========================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 14.99 |==================================================================== b . 13.53 |============================================================= c . 13.57 |============================================================== d . 13.12 |============================================================ oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 12.23 |==================================================================== b . 11.28 |=============================================================== c . 11.25 |=============================================================== d . 11.42 |=============================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 4.54904 |================================================================== b . 2.67147 |======================================= c . 2.68430 |======================================= d . 3.91928 |========================================================= oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 4.09180 |================================================================== b . 3.21993 |==================================================== c . 3.22719 |==================================================== d . 3.15380 |=================================================== oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 14822.50 |================================================================= b . 8683.31 |====================================== c . 8829.67 |======================================= d . 11688.60 |=================================================== oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 6396.75 |================================================================== b . 5454.56 |======================================================== c . 5902.15 |============================================================= d . 6177.94 |================================================================ oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 12541.9 |================================================================== b . 10488.7 |======================================================= c . 11586.7 |============================================================= d . 12187.5 |================================================================ oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 70.34 |==================================================================== b . 47.90 |============================================== c . 47.99 |============================================== d . 50.90 |================================================= oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 88.90 |==================================================================== b . 72.45 |======================================================= c . 61.66 |=============================================== d . 81.91 |=============================================================== oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 54.56 |==================================================================== b . 48.91 |============================================================= c . 48.67 |============================================================= d . 48.58 |============================================================= oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 6414.18 |================================================================== b . 5859.75 |============================================================ c . 5899.34 |============================================================= d . 6059.37 |============================================================== oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 12525.1 |================================================================== b . 11598.2 |============================================================= c . 11588.9 |============================================================= d . 12146.1 |================================================================ oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 6410.87 |================================================================== b . 5909.00 |============================================================= c . 5904.98 |============================================================= d . 6148.00 |===============================================================