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 > >
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