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Subject:	Re: Parallelization
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To:	cygwin AT cygwin DOT com
From:	Eliot Moss <moss AT cs DOT umass DOT edu>
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Date:	Mon, 18 Jul 2016 13:29:07 -0400
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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

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