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On 10 Jul 2014, at 05:19 pm, Ashwin Srinath <ashwinsrnth@gmail.com> wrote:
I'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, Ashwin
On Thu, Jul 10, 2014 at 6:08 AM, Sai Rajeshwar <rajsai24@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?
If your operations are using the BLAS functions a lot, you get SMP parallelisation for very cheap by linking to the multithreaded MKL or ACML versions and setting OMP_NUM_THREADS/MKL_NUM_THREADS to the no. of available cores. Cheers, Derek