Just a word to say that I find the glas benchmark results and design awesome!

https://github.com/libmir/mir

I am new to D but I think this kind of developments has the potential to attract a lot of people doing numerical computations.

I also would like to mention the "libFlame" approach used to describe and implement linear algebra algorithms like LU, Cholesky... decompositions.

https://www.cs.utexas.edu/~flame/web/methodology.html

IMHO the ndslice is a perfect match to benefit from this methodology.

I hope the best future for glas, it is very attractive.

Vincent

On Monday, 14 November 2016 at 07:42:13 UTC, Picaud Vincent wrote:
> Just a word to say that I find the glas benchmark results and design awesome!
>
> https://github.com/libmir/mir
>
> I am new to D but I think this kind of developments has the potential to attract a lot of people doing numerical computations.
>
> I also would like to mention the "libFlame" approach used to describe and implement linear algebra algorithms like LU, Cholesky... decompositions.
>
> https://www.cs.utexas.edu/~flame/web/methodology.html
>
> IMHO the ndslice is a perfect match to benefit from this methodology.
>
> I hope the best future for glas, it is very attractive.
>
> Vincent

Thank you, Vincent!

Yes, I will use libFlame approach, it is a really good. In the same time Dlang is more user-friendly for SIMD optimization. GLAS routines probably will follow hypothetical (it is closed source) Intel MKL approach but without unrolled loops. LibFLAME has 2 kinds of algorithms: blocking and unblocking. GLAS where it is possible will have 3 kinds: tiny unblocking, register (SIMD) blocking, and normal blocking.

Mir GLAS was moved to separate repo [1]. It is a "better C" library now. This means it is written in D but does not requre DRuntime. It also has standart BLAS API, so GLAS will be able to replace BLAS in already existing C / Fortran infrastructure.

[1] https://github.com/libmir/mir-glas

Best regards,
Ilya

On Monday, 14 November 2016 at 08:41:36 UTC, Ilya Yaroshenko wrote:

> Yes, I will use libFlame approach, it is a really good. In the same time Dlang is more user-friendly for SIMD optimization. GLAS routines probably will follow hypothetical (it is closed source) Intel MKL approach but without unrolled loops. LibFLAME has 2 kinds of algorithms: blocking and unblocking. GLAS where it is possible will have 3 kinds: tiny unblocking, register (SIMD) blocking, and normal blocking.

That is great!

I hope being able to use your lib soon,
Again thank you for sharing and for these impressive results!

Vincent