[Numpy-discussion] (no subject)

Ioan-Alexandru Lazar alexlz@lmn.pub...
Wed Jul 21 20:04:29 CDT 2010

Hello everyone,

I'm currently planning to use a Python-based infrastructure for our HPC
I've previously used NumPy and SciPy for basic scientific computing tasks,
performance hasn't been quite an issue for me until now. At the moment I'm
not too
sure as to what to do next though, and I was hoping that someone with more
experience in performance-related issues could point me to a way out of this.

The trouble lays in the following piece of code:

    w = 2 * math.pi * f
    M = A - (1j*w*E)
    n = M.shape[1]
    B1 = numpy.zeros(n)
    B2 = numpy.zeros(n)
    B1[n-2] = 1.0
    B2[n-1] = 1.0
-> slow part starts here
    x1 = umfpack.solve( um.UMFPACK_A, M, B1, autoTranspose = False)
    x2 = umfpack.solve( um.UMFPACK_A, M, B2, autoTranspose = False)
    solution = scipy.array([ [ x1[n-2], x2[n-2] ], [ x1[n-1], x2[n-1] ]])
    return solution

This isn't really too much -- it's generating a small

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