Changing the array to Fortran order using numpy.ndarray.T does not help much in my machine. But, this may be important since the LAPACK routines are written in Fortran 90.
On 2 April 2012 12:25, Nathaniel Smith <n...@pobox.com> wrote: > To see if this is an effect of numpy using C-order by default instead of > Fortran-order, try measuring eig(x.T) instead of eig(x)? > > -n > On Apr 1, 2012 2:28 PM, "Kamesh Krishnamurthy" <kames...@gmail.com> wrote: > >> Hello all, >> >> I profiled NumPy EIG and MATLAB EIG on the same Macbook pro, and both >> were linking to the Accelerate framework BLAS. NumPy turns out to be ~4x >> slower. I've posted details on Stackoverflow: >> http://stackoverflow.com/q/9955021/974568 >> >> Can someone please let me know the reason for the performance gap? >> >> Thanks, >> Kamesh >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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