Hi =,
About PyCUDA, scikits.cuda package uses PyCUDA to provide high-level functions similar to those in numpy. maybe you should check it out (at least for examples)!
[]'s--On Thu, Jul 10, 2014 at 12:19 PM, Ashwin Srinath <ashwinsrnth@gmail.com> wrote:
Hey, SaiI'm no expert, so I'll just share a few links to start this discussion. You definitely want to look at Cython if you're computing with NumPy arrays. If you're familiar with the MPI programming model, you want to check out mpi4py. If you have NVIDIA GPUs that you'd like to take advantage of, check out PyCUDA.
Thanks,AshwinOn Thu, Jul 10, 2014 at 6:08 AM, Sai Rajeshwar <rajsai24@gmail.com> wrote:
_______________________________________________1) Can Scipy take advantage of multi-cores.. if so howhi 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..
----------------------------------------------------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 RajeswarM-tech Computer TechnologyIIT Delhi
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Dayvid Victor R. de OliveiraPhD Candidate in Computer Science at Federal University of Pernambuco (UFPE)MSc in Computer Science at Federal University of Pernambuco (UFPE)BSc in Computer Engineering - Federal University of Pernambuco (UFPE)
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