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 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: 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: 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_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: 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: 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: 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: 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: 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 |============================================================= 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 |=============================================================== 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: 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: 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 |=============================================================== 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 |============================================================== 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 |================================================================ 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: 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: 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: 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: 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: 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: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3.56346 |================================================================== b . 2.16527 |======================================== c . 2.11974 |======================================= d . 2.08567 |=======================================