On Sat, Dec 24, 2011 at 3:46 PM, Michael Sioutis <[email protected]> wrote: > Hello! > > I haven't been following the list, cause I joined yesterday in order to > share my impressions > of PyPy here, so I don't know if these kinds of posts are frequent and > annoying.
Hi Michael They're more than welcome here. PyPy lacks a bit lots of success stories, so we definitely welcome each of them > > I'm using PyPy the last few weeks in a qualitative spatial reasoner I am > developing. The speedup is up to > 10 times over CPython, and it grows even more as the input size grows > bigger, but that's not what impressed > me the most, because I was expecting that. > > You can find in my presentation here at slides 25 and 33 some comparison > diagrams against C (red color) and C++ > (blue color) implementations of analogous reasoners. > I am using different data structures and slightly modified algorithms, so > you should not consider that the comparison > diagrams is upon the exact same piece of code. > Long story short, you will find out that the pypy reasoner ranks in > positions 1 and 2 respectively, and I believe it will > also rank 1 in the second diagram if I grow the input even more (I currently > don't have enough memory and the C implementation > tops it at 900 nodes, so it would be unreasonable and unfair to run on my > own). > > The impressive part of both diagrams is the scalability pypy offers me. It > starts slower than the statically compiled languages, > but the more you push the input sizes, the faster it goes compared to the > other two. > > I started developing the reasoner in python not necessarily to be fast in > timings, but because I want to go beyond the state of the art in > qualitative spatial reasoning and present sth new, so python was the > language of choice to do it fast, in terms of working hours :) > This is future work, that will be based on the current reasoner. > > Thank you for being patient, if you actually took the time to read my story, > and have a Merry Xmas! > Mike > > This is all very impressive! The reason why pypy "scales" well is probably because JIT takes time to kick in, so for the short-running examples it does not run at the full speed. It's really cool to see PyPy enabling people to do *really cool stuff* in Python, that was not entirely possible before. Makes us want to work harder :) Thanks for sharing this! Cheers, fijal _______________________________________________ pypy-dev mailing list [email protected] http://mail.python.org/mailman/listinfo/pypy-dev
