I don't think pypy is expected to speed up program where the majority of the time is spent in copy.deepcopy. The answer to this question is a bit boring one: don't write algorithms that copy around so much data.
As a general rule - if the vast majority of your work is done by the runtime there is no way for pypy to speed this up (mostly) and in fact the exact same algo in C would be as slow or slower. I'm sorry we can't give you a very good answer - if you really *NEED* to do that much copying (maybe you can make the copy more lazy?), then maybe shrinking the data structures would help? I can't answer that without having access to the code though, which I would be happy to look at. Cheers, fijal On Sat, May 14, 2016 at 1:19 AM, Eli Stevens (Gmail) <wickedg...@gmail.com> wrote: > Hello, > > I'm in the process of working on a hobby project to have an AI > searching through a game state space. I recently ran what I have so > far on pypy (I had been doing initial work on cpython), and got two > results that were unexpected: > > - The total execution time was basically identical between cpython and pypy > - The runtime on both pythons was about 50% copy.deepcopy (called on > the main game state object) > > The runtime of the script that I've been using is in the 30s to 2m > range, depending on config details, and the implementation fits the > following pretty well: > > """ > The JIT is generally good at speeding up straight-forward Python code > that spends a lot of time in the bytecode dispatch loop, i.e., running > actual Python code – as opposed to running things that only are > invoked by Python code. Good examples include numeric calculations or > any kind of heavily object-oriented program. > """ > > I have already pulled out constant game information (static info like > unit stats, etc.) into an object that isn't copied, and a lot of the > numerical data that is copied is stored in a numpy array so that I > don't have hundreds of dicts, ints, etc. > > First, is there a good way to speed up object copying? I've tried > pickling to a cache, and unpickling from there (so as to only pickle > once), but that didn't make a significant difference. > > http://vmprof.com/#/905dfb71d28626bff6341a5848deae73 (deepcopy) > http://vmprof.com/#/545f1243b345eb9e41d73a9043a85efd (pickle) > > Second, what's the best way to start figuring out why pypy isn't able > to outperform cpython on my program? > > Thanks for any pointers, > Eli > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org > https://mail.python.org/mailman/listinfo/pypy-dev _______________________________________________ pypy-dev mailing list pypy-dev@python.org https://mail.python.org/mailman/listinfo/pypy-dev
