Standard D, Mir D benchmarks against Numpy (BLAS)

[9il]

On Thursday, 12 March 2020 at 14:37:13 UTC, Pavel Shkadzko wrote:
> On Thursday, 12 March 2020 at 14:00:48 UTC, 9il wrote:
>> On Thursday, 12 March 2020 at 12:59:41 UTC, Pavel Shkadzko 
>> wrote:
>>> I have done several benchmarks against Numpy for various 2D 
>>> matrix operations. The purpose was mere curiosity and spread 
>>> the word about Mir D library among the office data engineers.
>>> Since I am not a D expert, I would be happy if someone could 
>>> take a second look and double check.
>>>
>>
>> Generally speaking, the D/Mir code of the benchmark is slow by 
>> how it has been written.
>> I am not arguing you to use  D/Mir. Furthermore, sometimes I 
>> am arguing my clients to do not to use it if you can. On the 
>> commercial request, I can write the benchmark or an applied 
>> algorithm so D/Mir will beat numpy in all the tests including 
>> gemm. --Ilya
>
> Didn't understand. You argue against D/Mir usage when talking 
> to your clients?

It depends on the problem they wanted me to solve.

> Actually, I feel like it is also useful to have unoptimized D 
> code benchmarked because this is how most people will write 
> their code when they first write it. Although, I can hardly 
> call these benchmarks unoptimized because I use LDC 
> optimization flags as well as some tips from you.

Agreed.  I just misunderstood the table at the forum, it was 
misaligned for me. The numbers look cool, thank you for the 
benchmark. Mir sorting looks slower then Phobos, it is 
interesting, and need a fix. You can use Phobos sorting with 
ndslice the same way with `each`.

Minor updates
https://github.com/tastyminerals/mir_benchmarks/pull/1