Frédéric, On Thu, Feb 7, 2013 at 11:31 AM, Frédéric Bastien <no...@nouiz.org> wrote: > Hi, > > I just read a paper[1] that compare python with numpy or pypy vs c++ and > fortran from a code, memory and speed point of view. The python code was > still better as you can't have list of ndarray in fortran and some other > stuff was harder to do. The fastest was fortran, then C++, but pypy around > 2x slower then c++. That isn't bad for a more productive development > language. > > Maybe you can check that article to find more case to compare.
Yes, I know about this article --- I've been in touch with Sylwester about it, as I found his code on github a few months ago, so we discussed it. I also CCed him if he wants to add some comments. The article is well balanced. To my taste, they use way too much OOP in the Fortran version, in fact I am bit surprised that Fortran was still the fastest, even with the OOP. But Sylwester was interested in comparing OOP approaches, so that's fair. If I have time (which I don't see likely soon, but who knows), I will see if I can write a simple direct non-OOP version of their Fortran code: https://github.com/slayoo/mpdata Possibly just by understanding the original reference [2] and see what datastructures/arrays I would use to implement it. In general however, I like their approach, that they took a real world method and not some artificial benchmark. So it's a very good contribution. Ondrej [2] Smolarkiewicz, P. K. (1984). A Fully Multidimensional Positive Definite Advection Transport Algorithm with Small Implicit Diffusion. Journal of Computational Physics, 54(2), 325–362. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
