On 01/23/2012 05:35 AM, Jonathan Rocher wrote:
Hi all,
I was reading this while learning about Pytables in more details and the origin of its efficiency. This sounds like a problem where out of core computation using pytables would shine since the dataset doesn't fit into CPU cache: http://www.pytables.org/moin/ComputingKernel. Of course C/Cythonizing the problem would be another good way...
Well, since the data certainly fits in RAM, one would use numexpr directly (which is what pytables also uses). Dag Sverre
HTH, Jonathan
2012/1/22 Ondřej Čertík <ondrej.certik@gmail.com <mailto:ondrej.certik@gmail.com>>
On Sun, Jan 22, 2012 at 3:13 AM, Sebastian Haase <seb.haase@gmail.com <mailto:seb.haase@gmail.com>> wrote: > How does the algorithm and timing compare to this one: > > http://code.google.com/p/priithon/source/browse/Priithon/mandel.py?spec=svna6117f5e81ec00abcfb037f0f9da2937bb2ea47f&r=a6117f5e81ec00abcfb037f0f9da2937bb2ea47f <http://code.google.com/p/priithon/source/browse/Priithon/mandel.py?spec=svna6117f5e81ec00abcfb037f0f9da2937bb2ea47f&r=a6117f5e81ec00abcfb037f0f9da2937bb2ea47f> > > The author of original version is Dan Goodman > # FAST FRACTALS WITH PYTHON AND NUMPY
Thanks Sebastian. This one is much faster ---- 2.7s on my laptop with the same dimensions/iterations.
It uses a better datastructures -- it only keeps track of points that still need to be iterated --- very clever. If I have time, I'll try to provide an equivalent Fortran version too, for comparison.
Ondrej _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org <mailto:NumPy-Discussion@scipy.org> http://mail.scipy.org/mailman/listinfo/numpy-discussion
-- Jonathan Rocher, PhD Scientific software developer Enthought, Inc. jrocher@enthought.com <mailto:jrocher@enthought.com> 1-512-536-1057 http://www.enthought.com <http://www.enthought.com/>
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