oneDNN Apple M2
Apple M2 testing with a Apple MacBook Air (13 h M2 2022) and llvmpipe on Arch rolling via the Phoronix Test Suite.


A: 

	Processor: Apple M2 @ 2.42GHz (4 Cores / 8 Threads), Motherboard: Apple MacBook Air (13 h M2 2022), Memory: 8GB, Disk: 251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256Z, Graphics: llvmpipe, Network: Broadcom Device 4433 + Broadcom Device 5f71

	OS: Arch rolling, Kernel: 5.19.0-rc7-asahi-2-1-ARCH (aarch64), Desktop: KDE Plasma 5.25.4, Display Server: X Server 1.21.1.4, OpenGL: 4.5 Mesa 22.1.6 (LLVM 14.0.6 128 bits), Compiler: GCC 12.1.0 + Clang 14.0.6, File-System: ext4, Screen Resolution: 2560x1600

B: 

	Processor: Apple M2 @ 2.42GHz (4 Cores / 8 Threads), Motherboard: Apple MacBook Air (13 h M2 2022), Memory: 8GB, Disk: 251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256Z, Graphics: llvmpipe, Network: Broadcom Device 4433 + Broadcom Device 5f71

	OS: Arch rolling, Kernel: 5.19.0-rc7-asahi-2-1-ARCH (aarch64), Desktop: KDE Plasma 5.25.4, Display Server: X Server 1.21.1.4, OpenGL: 4.5 Mesa 22.1.6 (LLVM 14.0.6 128 bits), Compiler: GCC 12.1.0 + Clang 14.0.6, File-System: ext4, Screen Resolution: 2560x1600

C: 

	Processor: Apple M2 @ 2.42GHz (4 Cores / 8 Threads), Motherboard: Apple MacBook Air (13 h M2 2022), Memory: 8GB, Disk: 251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256Z, Graphics: llvmpipe, Network: Broadcom Device 4433 + Broadcom Device 5f71

	OS: Arch rolling, Kernel: 5.19.0-rc7-asahi-2-1-ARCH (aarch64), Desktop: KDE Plasma 5.25.4, Display Server: X Server 1.21.1.4, OpenGL: 4.5 Mesa 22.1.6 (LLVM 14.0.6 128 bits), Compiler: GCC 12.1.0 + Clang 14.0.6, File-System: ext4, Screen Resolution: 2560x1600


oneDNN 2.7
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 36.56 |===================================================================
B . 37.23 |====================================================================
C . 36.82 |===================================================================


oneDNN 2.7
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 267.76 |===================================================================
B . 266.96 |===================================================================
C . 264.62 |==================================================================


oneDNN 2.7
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 42.22 |====================================================================
B . 42.39 |====================================================================
C . 42.40 |====================================================================


oneDNN 2.7
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 38.67 |====================================================================
B . 38.77 |====================================================================
C . 38.80 |====================================================================


oneDNN 2.7
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 174.20 |===================================================================
B . 174.55 |===================================================================
C . 174.01 |===================================================================


oneDNN 2.7
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 58.20 |====================================================================
B . 58.33 |====================================================================
C . 58.37 |====================================================================


oneDNN 2.7
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 27.15 |====================================================================
B . 27.21 |====================================================================
C . 27.20 |====================================================================


oneDNN 2.7
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 34.19 |====================================================================
B . 34.13 |====================================================================
C . 34.13 |====================================================================


oneDNN 2.7
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 175.80 |===================================================================
B . 175.51 |===================================================================
C . 175.67 |===================================================================


oneDNN 2.7
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 16519.6 |==================================================================
B . 16493.3 |==================================================================
C . 16513.1 |==================================================================


oneDNN 2.7
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 16505.9 |==================================================================
B . 16512.6 |==================================================================
C . 16498.2 |==================================================================


oneDNN 2.7
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
A . 32230.4 |==================================================================
B . 32239.0 |==================================================================
C . 32211.4 |==================================================================


oneDNN 2.7
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 48.58 |====================================================================
B . 48.54 |====================================================================
C . 48.55 |====================================================================


oneDNN 2.7
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 32236.5 |==================================================================
B . 32211.7 |==================================================================
C . 32214.7 |==================================================================


oneDNN 2.7
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 16.94 |====================================================================
B . 16.93 |====================================================================
C . 16.94 |====================================================================


oneDNN 2.7
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
A . 32230.2 |==================================================================
B . 32237.6 |==================================================================
C . 32226.7 |==================================================================


oneDNN 2.7
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
A . 16512.7 |==================================================================
B . 16511.2 |==================================================================
C . 16515.5 |==================================================================


oneDNN 2.7
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
A . 109.75 |===================================================================
B . 95.11  |==========================================================
C . 94.85  |==========================================================