Improve performance with ARM SIMD on Cortex-M4 and more powerfull cores

[qywx]

Let's discuss how can we improve the performance of this library. I expect to use arm_math.h rather than ASM.

[gbmhunter]

Hi @SledgeH . Thanks for raising an issue! Can you please elaborate more on what you are after?

I had a look into what arm_math.h is, at it seems it is a bunch of signal processing functions for ARM Cortex M* devices?

https://github.com/ARM-software/CMSIS/blob/master/CMSIS/Include/arm_math.h

[qywx]

Yes it is. The aim (one of main) of arm_math.h is to wrap SIMD ability. Here is CMSIS documentation of the CMSIS library.
arm_add_q31.c shows ARM SIMD implementation. This is a simple function, but there are others more complicated.
As far as I understood ARM Cortex M core has 4 SIMD conveyors. So we will achieve ~4x acceleration on array processing.

This is actual for ARM cores with SIMD ability CM3 and CM4 and may be CM7.

[gbmhunter]

@SledgeH , o.k., so it allows you to do parallel processing, as long as the instruction is the same.

How do you see this as being a benefit to this library? What is a real-world example of what you want to call in code, and what to expect in return?

[qywx]

Now I think it is enough to add C++ bindings for arm_math and pass Q classes to the math functions, which will convert ninja Q to arm Q.
I will create pull request ones it'll be done. Or create another one header lib on top of yours and ARM's.
Thank you for dialog.