Hi Pauli, thanks for the quick answer. Is there a way to check the optimization flags of numpy after installation?
I am away of a matlab installation now, but I remember I saw a single processor active with matlab. I will check it again soon Thanks! El 19/07/2011, a las 13:10, Pauli Virtanen <p...@iki.fi> escribió: > Tue, 19 Jul 2011 11:05:18 +0200, Carlos Becker wrote: >> Hi, I started with numpy a few days ago. I was timing some array >> operations and found that numpy takes 3 or 4 times longer than >> Matlab on >> a simple array-minus-scalar operation. >> This looks as if there is a lack of vectorization, even though this >> is >> just a guess. I hope this is not reposting. I tried searching the >> mailing list database but did not find anything related >> specifically to >> a problem like this one. > > I see essentially no performance difference: > > Matlab [7.10.0.499 (R2010a)]: 0.0321 > Numpy [1.6.0]: 0.03117567 > > If later versions of Matlab can parallelize the computation across > multiple processors, that could be one possibility for the difference > you see. Alternatively, you may have compiled Numpy with optimizations > turned off. > > _______________________________________________ > 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
