Thanks all for valuable feedback. I will first explore the fastest fft
independent from theano. I have been playing with Mac's Accelerate
Framework. It seems pretty well tuned. I could not beat it's performance
using mkl or fftw. I will look into that more carefully and try to post a
systematic result comparing those.

Thanks again,
Best,
Cha.

On Wed, Apr 19, 2017 at 9:05 PM, Patric <[email protected]> wrote:

> btw, as @Jesse mentioned, the Intel distribution Python already includes
> Theano w/ performance improvements out of the box :)
>
> Intel-optimized Deep Learning
> .. Update 2 incorporates two Intel-optimized Deep Learning frameworks,
> Caffe* and Theano*, into the distribution so Python users can take
> advantage of these optimizations out of the box.
>
>
> On Thursday, April 20, 2017 at 2:12:40 AM UTC+8, Jesse Livezey wrote:
>>
>> From tests I've done, the MKL fft library is comparable and sometimes
>> faster than the FFTW package. Both are much faster than the numpy fft. It's
>> available in the accelerate package from Continuum (mkl conda package only
>> has blas).
>>
>> It also looks like intel has a free conda channel, which builds scipy and
>> numpy against MKL
>> https://software.intel.com/en-us/forums/intel-distribution-f
>> or-python/topic/713736
>>
>> On Wednesday, April 19, 2017 at 10:54:33 AM UTC-7, nouiz wrote:
>>>
>>> Blas won't help for fft. So you would need a faster fft library then
>>> what we use and modify the perform() method of those ops to use that new
>>> lib.
>>>
>>> FFTW is one possible faster implementation. There is others. I can't
>>> comment on which one would be better. Search the web, I recall seeing some
>>> people comparing fft lib that is available in python.
>>>
>>> If you modify those ops for that, pushing upstream those change would be
>>> great.
>>>
>>> Fred
>>>
>>>
>>>
>>> On Tue, Apr 18, 2017 at 12:16 PM <[email protected]> wrote:
>>>
>>>> Hi,
>>>>
>>>> I have implemented a layer which uses functions theano.tensor.fft.rfft
>>>> and theano.tensor.fft.irfft. What might be the best way to improve the
>>>> speed of that layer on cpu? Installing FFTW, an optimized BLAS library?
>>>>
>>>> Thanks
>>>> Cha.
>>>>
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