I recently found out there is support for vector extensions
But I have found I don't really understand how to use it, not even mentioning the more complex stuff. I couldn't find any good examples either.

I'm trying to figure out how to implement the following opBinary using vector extensions.

alias MatType = typeof(this);

union{
  T[rows*columns] vec;
  T[rows][columns] mat;
}

MatType opBinary(string op, T)(const T right) const {
  MatType result = this;
  mixin("result.vec[] = this.vec[] " ~ op ~ " right;");
  return result;
}

Or alternatively, as I'm not sure which is more efficient/faster:

MatType opBinary(string op, T)(const T right) const {
  MatType result;
  static foreach(i; 0..rows*columns)
    mixin("result.vec[i] = this.vec[i] " ~ op ~ " right;");
  return result;
}

But going off the documentation, I have no idea how to use vector extensions to achieve something like this.

As a small disclaimer; I don't know to what extent the compiler already automates these kind of operations, and mostly want to use this as a learning experience.

Kind regards, HN

On Sunday, 17 April 2022 at 11:16:25 UTC, HuskyNator wrote:

alias MatType = typeof(this);

union{
  T[rows*columns] vec;
  T[rows][columns] mat;
}

MatType opBinary(string op, T)(const T right) const {
  MatType result = this;
  mixin("result.vec[] = this.vec[] " ~ op ~ " right;");
  return result;
}

MatType opBinary(string op, T)(const T right) const {
  MatType result;
  static foreach(i; 0..rows*columns)
    mixin("result.vec[i] = this.vec[i] " ~ op ~ " right;");
  return result;
}

I'd experiment with CompilerExplorer. For example this shows that the codegen is identical for both opBinary version for "+".

About time spent to compile, static foreach is known not to scale well.

On Sunday, 17 April 2022 at 11:16:25 UTC, HuskyNator wrote:

You might want to have a look at https://code.dlang.org/packages/intel-intrinsics

— Bastiaan.

On Sunday, 17 April 2022 at 17:04:57 UTC, Bastiaan Veelo wrote:

This does not discuss core.simd or __vector type, or did I miss/mininterpret something?

On Thursday, 21 April 2022 at 15:31:04 UTC, HuskyNator wrote:

It wraps core.simd with an eye on portability. I haven’t used it myself, but my impression is that if you’re interested in core.simd, intel-intrinsics may be a better option. I think there is also better documentation. There is a video of a DConf presentation that you may want to watch.

— Bastiaan.

On Sunday, 17 April 2022 at 11:16:25 UTC, HuskyNator wrote:

For your particular case, it is very likely LDC and GDC will be able to optimize your loops using SIMD.