[pypy-dev] Game state search dominated by copy.deepcopy

[Eli Stevens (Gmail)]

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