onednn 3.1 tigerlake
Intel Core i7-1165G7 testing with a Dell 0GG9PT (3.11.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.10 via the Phoronix Test Suite.


a: 

	Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.11.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

	OS: Ubuntu 22.10, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4 + Wayland, OpenGL: 4.6 Mesa 22.2.5, OpenCL: OpenCL 3.0, Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1200

b: 

	Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.11.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

	OS: Ubuntu 22.10, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4 + Wayland, OpenGL: 4.6 Mesa 22.2.5, OpenCL: OpenCL 3.0, Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1200

c: 

	Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.11.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

	OS: Ubuntu 22.10, Kernel: 5.19.0-38-generic (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4 + Wayland, OpenGL: 4.6 Mesa 22.2.5, OpenCL: OpenCL 3.0, Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1200


oneDNN 3.1
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 7.43755 |=================================================================
b . 7.52319 |==================================================================
c . 6.70311 |===========================================================


oneDNN 3.1
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 5.72636 |=================================================================
b . 5.80411 |==================================================================
c . 5.68653 |=================================================================


oneDNN 3.1
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 1.58645 |=================================================================
b . 1.59346 |==================================================================
c . 1.60082 |==================================================================


oneDNN 3.1
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 2.20666 |================================================================
b . 2.28981 |==================================================================
c . 2.20832 |================================================================


oneDNN 3.1
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 19.09 |====================================================================
b . 19.13 |====================================================================
c . 18.26 |=================================================================


oneDNN 3.1
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 5.83118 |===============================================================
b . 6.12705 |==================================================================
c . 5.80452 |===============================================================


oneDNN 3.1
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 8.79583 |==================================================================
b . 8.84187 |==================================================================
c . 8.56588 |================================================================


oneDNN 3.1
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 12.98 |====================================================================
b . 11.95 |==============================================================
c . 13.06 |====================================================================


oneDNN 3.1
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 10.60 |====================================================================
b . 10.65 |====================================================================
c . 10.27 |==================================================================


oneDNN 3.1
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 7.96507 |==================================================================
b . 7.97341 |==================================================================
c . 7.76888 |================================================================


oneDNN 3.1
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 2.15004 |==================================================================
b . 2.16516 |==================================================================
c . 2.16487 |==================================================================


oneDNN 3.1
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 2.53561 |==================================================================
b . 2.54368 |==================================================================
c . 2.51699 |=================================================================


oneDNN 3.1
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 7448.89 |==================================================================
b . 7499.70 |==================================================================
c . 7479.15 |==================================================================


oneDNN 3.1
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 3852.88 |==================================================================
b . 3850.94 |==================================================================
c . 3857.92 |==================================================================


oneDNN 3.1
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 8260.44 |==================================================================
b . 7604.92 |=============================================================
c . 7194.33 |=========================================================


oneDNN 3.1
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 38.60 |==========================================================
b . 39.11 |===========================================================
c . 45.12 |====================================================================


oneDNN 3.1
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 84.73 |====================================================================
b . 46.88 |======================================
c . 52.22 |==========================================


oneDNN 3.1
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 39.28 |====================================================================
b . 37.49 |=================================================================
c . 37.51 |=================================================================


oneDNN 3.1
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 3849.51 |==================================================================
b . 3857.97 |==================================================================
c . 3848.60 |==================================================================


oneDNN 3.1
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 7629.39 |==================================================================
b . 7626.55 |==================================================================
c . 7631.13 |==================================================================


oneDNN 3.1
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 3859.67 |==================================================================
b . 3858.62 |==================================================================
c . 3851.35 |==================================================================