[SciPy-Dev] scipy improve performance by parallelizing

[Eric Moore]

On Thursday, July 24, 2014, Sai Rajeshwar <rajsai24 at gmail.com> wrote:

> hi julian thanks..
>
> but when i use numpy.convolve  i get this error  ValueError: object too
> deep for desired array
>
> does numpy.convolve work for 2D or 3D convolution?
> thanks
>
> *with regards..*
>
> *M. Sai Rajeswar*
> *M-tech  Computer Technology*
>
>
> *IIT Delhi----------------------------------Cogito Ergo Sum---------*
>
>
> On Fri, Jul 11, 2014 at 11:13 PM, Julian Taylor <
> jtaylor.debian at googlemail.com
> <javascript:_e(%7B%7D,'cvml','jtaylor.debian at googlemail.com');>> wrote:
>
>> for simple convolutions there is also np.convolve
>>
>> compared to scipy it releases the GIL and you can use normal python
>> threads for parallization if you need to compute many independent
>> convolutions and not just one.
>>
>> That said scipy should probably release the GIL too, probably a bug that
>> it doesn't.
>>
>> On 10.07.2014 17:19, Ashwin Srinath wrote:
>> > Hey, Sai
>> >
>> > I'm no expert, so I'll just share a few links to start this discussion.
>> > You definitely want to look at Cython <http://cython.org/> if you're
>> > computing with NumPy arrays. If you're familiar with the MPI programming
>> > model, you want to check out mpi4py <http://mpi4py.scipy.org/>. If you
>> > have NVIDIA GPUs that you'd like to take advantage of, check out PyCUDA
>> > <http://mathema.tician.de/software/pycuda/>.
>> >
>> > Thanks,
>> > Ashwin
>> >
>> >
>> > On Thu, Jul 10, 2014 at 6:08 AM, Sai Rajeshwar <rajsai24 at gmail.com
>> <javascript:_e(%7B%7D,'cvml','rajsai24 at gmail.com');>
>> > <mailto:rajsai24 at gmail.com
>> <javascript:_e(%7B%7D,'cvml','rajsai24 at gmail.com');>>> wrote:
>> >
>> >     hi all,
>> >
>> >        im trying to optimise a python code takes huge amount of time on
>> >     scipy functions such as scipy.signa.conv. Following are some of my
>> >     queries regarding the same.. It would be great to hear from you..
>> >     thanks..
>> >     ----------------------------------------------------
>> >       1) Can Scipy take advantage of multi-cores.. if so how
>> >     2)what are ways we can improve the performance of scipy/numpy
>> >     functions eg: using openmp, mpi etc
>> >     3)If scipy internally use blas/mkl libraries can we enable
>> >     parallelism through these?
>> >
>> >
>> >     looks like i have to work on internals of scipy.. thanks a lot..
>> >
>> >
>> >     *with regards..*
>> >     *
>> >     *
>> >     *M. Sai Rajeswar*
>> >     *M-tech  Computer Technology*
>> >     *IIT Delhi
>> >     ----------------------------------Cogito Ergo Sum---------
>> >     *
>> >
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>> >
>> >
>> >
>> >
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>
>

There are also convolution functions in scipy.ndimage. For simple smallish
1d convolution ndimage is much much faster than scipy.signal and somewhat
faster than numpy.convolve.
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