Awesome information! I'll start taking a look through all of this and let you know what I can improve.
-----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Michael Foord Sent: Thursday, August 14, 2008 6:15 AM To: Discussion of IronPython Subject: [IronPython] Performance of IronPython 2 Beta 4 and IronPython 1 Hello all, I've ported Resolver One to run on IronPython 2 Beta 4 to check for any potential problems (we will only do a *proper* port once IP 2 is out of beta). The basic porting was straightforward and several bugs have been fixed since IP 2 B3 - many thanks to the IronPython team. The good news is that Resolver One is only 30-50% slower than Resolver One on IronPython 1! (It was 300 - 400% slower on top of IP 2 B3.) Resolver One is fairly heavily optimised around the performance hotspots of IronPython 1, so we expect to have to do a fair bit of profiling and refactoring to readjust to the performance profile of IP 2. Having said that, there are a few oddities (and the areas that slow down vary tremendously depending on which spreadsheet we use to benchmark it - making it fairly difficult to track down the hotspots). We have one particular phase of spreadsheet calculation that takes 0.4seconds on IP1 and around 6 seconds on IP2, so I have been doing some micro-benchmarking to try and identify the hotspot. I've certainly found part of the problem. For those that are interested I've attached the very basic microbenchmarks I've been using. The nice thing is that in *general* IP2 does outperform IP1. The results that stand out in the other direction are: Using sets with custom classes (that define '__eq__', '__ne__' and '__hash__') seems to be 6 times slower in IronPython 2. Adding lists together is about 50% slower. Defining functions seems to be 25% slower and defining old style classes about 33% slower. (Creating instances of new style classes is massively faster though - thanks!) The code I used to test sets (sets2.py) is as follows: from System import DateTime class Thing(object): def __init__(self, val): self.val = val def __eq__(self, other): return self.val == other.val def __neq__(self): return not self.__eq__(other) def __hash__(self): return hash(self.val) def test(s): a = set() for i in xrange(100000): a.add(Thing(i)) a.add(Thing(i+1)) Thing(i) in a Thing(i+2) in a return (DateTime.Now -s).TotalMilliseconds s = DateTime.Now print test(s) Interestingly the time taken is exactly the same if I remove the definition of '__hash__'. The full set of results below: Results in milliseconds with a granularity of about 15ms and so an accuracy of +/- ~60ms. All testing with 10 000 000 operations unless otherwise stated. Empty loop (overhead): IP1: 421.9 IP2: 438 Create instance newstyle: IP1: 20360 IP2: 1109 Create instance oldstyle: IP1: 3766 IP2: 3359 Function call: IP1: 937 IP2: 906 Create function: 25% slower IP1: 2828 IP2: 3640 Define newstyle (1 000 000): IP1: 42047 IP2: 20484 Define oldstyle (1 000 000): 33% slower IP1: 1781 IP2: 2671 Comparing (== and !=): IP1: 278597 IP2: 117662 Sets (with numbers): IP1: 37095 IP2: 30860 Lists (10 000): 50% slower IP1: 10422 IP2: 16109 Recursion (10 000): IP1: 1125 IP2: 1000 Sets2 (100 000): 600% slower IP1: 4984 IP2: 30547 I'll be doing more as the 600% slow down for sets and the 50% slow down for lists accounts for some of the dependency analysis problem but not all of it. Many Thanks Michael Foord -- http://www.resolversystems.com http://www.ironpythoninaction.com Sample disclaimer text _______________________________________________ Users mailing list Users@lists.ironpython.com http://lists.ironpython.com/listinfo.cgi/users-ironpython.com
