oneDNN 2.0 Intel Tiger Lake
Intel Core i7-1165G7 testing with a Dell 0GG9PT (1.0.3 BIOS) and Intel UHD 3GB on Ubuntu 20.10 via the Phoronix Test Suite.


Run 1: 

	Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (1.0.3 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel UHD 3GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

	OS: Ubuntu 20.10, Kernel: 5.10.0-051000rc7daily20201213-generic (x86_64) 20201212, Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.6 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1200

Run 2: 

	Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (1.0.3 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel UHD 3GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

	OS: Ubuntu 20.10, Kernel: 5.10.0-051000rc7daily20201213-generic (x86_64) 20201212, Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.6 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1200

Run 3: 

	Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (1.0.3 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel UHD 3GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201

	OS: Ubuntu 20.10, Kernel: 5.10.0-051000rc7daily20201213-generic (x86_64) 20201212, Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.6 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1200


oneDNN 2.0
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 12.20 |================================================================
Run 2 . 12.23 |================================================================
Run 3 . 12.29 |================================================================


oneDNN 2.0
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 6.43606 |========================================================
Run 2 . 6.44613 |========================================================
Run 3 . 7.17560 |==============================================================


oneDNN 2.0
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 2.48937 |=========================================================
Run 2 . 2.49932 |=========================================================
Run 3 . 2.70714 |==============================================================


oneDNN 2.0
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 2.84008 |=========================================================
Run 2 . 2.85308 |=========================================================
Run 3 . 3.11496 |==============================================================


oneDNN 2.0
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 25.56 |==============================================================
Run 2 . 25.76 |===============================================================
Run 3 . 26.35 |================================================================


oneDNN 2.0
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 7.92055 |=========================================================
Run 2 . 8.29222 |============================================================
Run 3 . 8.63478 |==============================================================


oneDNN 2.0
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 13.50 |==========================================================
Run 2 . 14.96 |================================================================
Run 3 . 14.11 |============================================================


oneDNN 2.0
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 14.10 |============================================================
Run 2 . 14.94 |================================================================
Run 3 . 14.92 |================================================================


oneDNN 2.0
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 11.35 |============================================================
Run 2 . 12.12 |================================================================
Run 3 . 12.15 |================================================================


oneDNN 2.0
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 9.64780  |==========================================================
Run 2 . 10.09398 |=============================================================
Run 3 . 10.07588 |=============================================================


oneDNN 2.0
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 3.00801 |===========================================================
Run 2 . 3.16932 |==============================================================
Run 3 . 3.17051 |==============================================================


oneDNN 2.0
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 2.74299 |===========================================================
Run 2 . 2.88129 |==============================================================
Run 3 . 2.89264 |==============================================================


oneDNN 2.0
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 8928.89 |===========================================================
Run 2 . 9301.85 |==============================================================
Run 3 . 9350.26 |==============================================================


oneDNN 2.0
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 4570.32 |===========================================================
Run 2 . 4793.37 |==============================================================
Run 3 . 4799.77 |==============================================================


oneDNN 2.0
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 9072.26 |============================================================
Run 2 . 9309.37 |==============================================================
Run 3 . 9315.57 |==============================================================


oneDNN 2.0
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 50.89 |==============================================================
Run 2 . 51.97 |================================================================
Run 3 . 52.12 |================================================================


oneDNN 2.0
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 59.94 |==============================================================
Run 2 . 61.73 |================================================================
Run 3 . 61.15 |===============================================================


oneDNN 2.0
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 37.75 |========================================================
Run 2 . 42.82 |================================================================
Run 3 . 42.79 |================================================================


oneDNN 2.0
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 4537.86 |==========================================================
Run 2 . 4799.98 |==============================================================
Run 3 . 4809.37 |==============================================================


oneDNN 2.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 4.96366 |==========================================================
Run 2 . 5.35102 |==============================================================
Run 3 . 5.35007 |==============================================================


oneDNN 2.0
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 8891.89 |===========================================================
Run 2 . 9302.70 |==============================================================
Run 3 . 9299.60 |==============================================================


oneDNN 2.0
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 4532.64 |==========================================================
Run 2 . 4807.71 |==============================================================
Run 3 . 4816.40 |==============================================================


oneDNN 2.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
Run 1 . 2.74771 |=========================================================
Run 2 . 2.99320 |==============================================================
Run 3 . 3.00553 |==============================================================


oneDNN 2.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
Run 1 . 12.06 |=============================================================
Run 2 . 12.66 |================================================================
Run 3 . 12.71 |================================================================