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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2107150-IB-ONEDNN11860
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 |================================================================