[SciPy-dev] FFTW performances in scipy and numpy

[David M. Cooke]

"John Travers" <jtravs@gmail.com> writes:

> On 01/08/07, David Cournapeau <david@ar.media.kyoto-u.ac.jp> wrote:
>>
>> 3 strategies are available:
>>     - Have a flag to check whether the given array is 16 bytes aligned,
>> and conditionnally build plans using this info
>>     - Use FFTW_UNALIGNED, and do not care about alignement
>>     - Current strategy: copy.
>>
>> The three strategies use FFTW_MEASURE, which I didn't do before, and may
>
> Another strategy worth trying is using FFTW_MEASURE once and then
> using FFTW_ESTIMATE for additional arrays. FFTW accumulates wisdom and
> so the initial call with MEASURE means that further estimated plans
> also benefit. In my simple tests it comes very close to measuring for
> each individual array.

We could also cache the wisdom in a file using the guru interface, so
that you could do even do a FFTW_PATIENT once.

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|David M. Cooke              http://arbutus.physics.mcmaster.ca/dmc/
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