Parallelization

[Eliot Moss]

On 7/18/2016 1:38 AM, Tony Kelman wrote:
> Eliot Moss <moss <at> cs.umass.edu> writes:
>
>> True ... it also made me think of Python, which is designed to use
>> parallelized numpy (etc.) libraries, optimized for your platform.
>> Can use all the hardware threads on your machine, as well as make
>> good use of vector extensions such as AVX.  A 64-bit (x86-64)
>> version will give best use of vector processing, in my
>> experience.
>>
>> Regards -- Eliot Moss
>
> numpy is only as parallel as the underlying BLAS/LAPACK library that
> it uses is. So if you're using Cygwin's openblas then you're in
> decent shape. But I don't think cv_adams spends much time (if any?)
> in BLAS/LAPACK dense linear algebra functions, I think it's mostly
> dominated by function evaluation time.

Ok -- I'm not sure what to suggest then ...

Regards -- EM

--
Problem reports:       http://cygwin.com/problems.html
FAQ:                   http://cygwin.com/faq/
Documentation:         http://cygwin.com/docs.html
Unsubscribe info:      http://cygwin.com/ml/#unsubscribe-simple