Mir GLAS vs Intel MKL: which is faster?

[Andrei Alexandrescu via Digitalmars-d]

On 09/24/2016 10:26 AM, jmh530 wrote:
> On Saturday, 24 September 2016 at 13:49:35 UTC, Andrei Alexandrescu wrote:
>>
>> I see, thanks. To the extent the Python-specific overheads are
>> measurable, it might make sense to include the benchmark.
>>
>
> Here are some benchmarks from Eigen and Blaze for comparison
> http://eigen.tuxfamily.org/index.php?title=Benchmark
> https://bitbucket.org/blaze-lib/blaze/wiki/Benchmarks
>
> They don't include Python, for the reason mentioned above (no one would
> use native python implementation of matrix multiplication, it just calls
> some other library).
>
> I don't see a reason to include it here.

OK. Yah, native Python wouldn't make sense. It may be worth mentioning 
that SciPy uses BLAS so it has the same performance profile.

Also, a great idea for a followup would be a blog post comparing the 
source code for a typical linear algebra real-world task. The idea 
being, yes the D version has parity with Intel, but there _is_ a reason 
to switch to it because of its ease of use.


Andrei