I did the computation
on this computer using a slightly modified version of
DMetalKong's Python code.
Python 2.7.5
SciPy 0.12.0
NumPy 1.7.1
Code:
>>> import numpy
>>> import time
>>> import scipy
>>> import scipy.sparse
>>> import scipy.sparse.linalg
>>>
>>> # Read N & d ...
... start = time.time()
>>> N = numpy.loadtxt(open('E:\z\N.dat'))
>>> d = numpy.loadtxt(open('E:\z\d.dat'))
>>> end = time.time()
>>> print "%f seconds" % (end-start)
6.532000 seconds
>>>
>>> # solve...
... start = time.time()
>>> x = numpy.linalg.solve(N,d)
>>> end = time.time()
>>> print "%f seconds" % (end-start)
15.281000 seconds
>>>
>>> # Convert to sparse...
... start = time.time()
>>> Ns = scipy.sparse.csr_matrix(N)
>>> end = time.time()
>>> print "%f seconds" % (end-start)
0.234000 seconds
>>>
>>> # solve sparse...
... start = time.time()
>>> xs = scipy.sparse.linalg.spsolve(Ns,d)
>>> end = time.time()
>>> print "%f seconds" % (end-start)
0.453000 seconds
>>>
I had expected Python to be
at least as fast as SciLab.
Perhaps there's an MKL for Python I need to install?