onednn 1185G7 Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.0.3 BIOS) and Intel Xe TGL GT2 3GB on Ubuntu 21.04 via the Phoronix Test Suite. 1: Processor: Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads), Motherboard: Dell 0DXP1F (3.0.3 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Micron 2300 NVMe 512GB, Graphics: Intel Xe TGL GT2 3GB (1350MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 OS: Ubuntu 21.04, Kernel: 5.13.0-051300-generic (x86_64), Desktop: GNOME Shell 3.38.4, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 21.2.0-devel (git-dd98918 2021-07-12 hirsute-oibaf-ppa), Vulkan: 1.2.182, Compiler: GCC 10.3.0, File-System: ext4, Screen Resolution: 1920x1200 2: Processor: Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads), Motherboard: Dell 0DXP1F (3.0.3 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Micron 2300 NVMe 512GB, Graphics: Intel Xe TGL GT2 3GB (1350MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 OS: Ubuntu 21.04, Kernel: 5.13.0-051300-generic (x86_64), Desktop: GNOME Shell 3.38.4, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 21.2.0-devel (git-dd98918 2021-07-12 hirsute-oibaf-ppa), Vulkan: 1.2.182, Compiler: GCC 10.3.0, File-System: ext4, Screen Resolution: 1920x1200 3: Processor: Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads), Motherboard: Dell 0DXP1F (3.0.3 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Micron 2300 NVMe 512GB, Graphics: Intel Xe TGL GT2 3GB (1350MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 OS: Ubuntu 21.04, Kernel: 5.13.0-051300-generic (x86_64), Desktop: GNOME Shell 3.38.4, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 21.2.0-devel (git-dd98918 2021-07-12 hirsute-oibaf-ppa), Vulkan: 1.2.182, Compiler: GCC 10.3.0, File-System: ext4, Screen Resolution: 1920x1200 oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 11.51 |==================================================================== 2 . 11.52 |==================================================================== 3 . 11.54 |==================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6.45882 |=========================================================== 2 . 6.48767 |=========================================================== 3 . 7.24078 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.41309 |============================================================= 2 . 2.41590 |============================================================= 3 . 2.59401 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.78481 |=========================================================== 2 . 2.78597 |=========================================================== 3 . 3.11593 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 25.38 |=================================================================== 2 . 25.39 |=================================================================== 3 . 25.86 |==================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 7.73083 |=================== 2 . 7.82006 |==================== 3 . 25.98626 |================================================================= oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 13.12 |==================================================================== 2 . 13.14 |==================================================================== 3 . 13.07 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 14.21 |==================================================================== 2 . 13.91 |=================================================================== 3 . 13.88 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 11.36 |==================================================================== 2 . 11.25 |=================================================================== 3 . 11.26 |=================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 9.65443 |================================================================== 2 . 9.64037 |================================================================== 3 . 9.61514 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.99331 |================================================================== 2 . 2.98337 |================================================================== 3 . 2.99665 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.70143 |================================================================== 2 . 2.69884 |================================================================== 3 . 2.69537 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 8885.95 |================================================================== 2 . 8875.65 |================================================================== 3 . 8884.92 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4560.81 |============================================================= 2 . 4915.80 |================================================================== 3 . 4562.59 |============================================================= oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 8879.39 |=============================================================== 2 . 9309.74 |================================================================== 3 . 8885.72 |=============================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 51.26 |=================================================================== 2 . 52.11 |==================================================================== 3 . 51.23 |=================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 56.61 |================================================================== 2 . 58.52 |==================================================================== 3 . 56.70 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 41.13 |=================================================================== 2 . 41.54 |==================================================================== 3 . 40.90 |=================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4560.69 |============================================================== 2 . 4855.10 |================================================================== 3 . 4564.07 |============================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.79333 |============================================================== 2 . 5.12274 |================================================================== 3 . 4.80231 |============================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 8872.45 |=============================================================== 2 . 9294.00 |================================================================== 3 . 8881.77 |=============================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 4561.54 |============================================================== 2 . 4850.57 |================================================================== 3 . 4566.99 |============================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.79809 |============================================================= 2 . 3.00737 |================================================================== 3 . 2.76633 |============================================================= oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 11.86 |================================================================ 2 . 12.55 |==================================================================== 3 . 11.90 |================================================================