[IronPython] Generator Performance (IronPython vs. CPython(

[henry show]

can't wait to try beta5 out.

2006/3/18, Dino Viehland <dinov at exchange.microsoft.com>:
>
> The good news this is basically the same issue.  The better news is I've
> got a fix that gets us performance that's pretty much equal to CPython that
> will be in Beta 5 for both this and the other generator case.
>
> Thanks for reporting these.  If you (or anyone else) has other issues
> they'd like to point out now's a great time, keep them coming!
>
>
> Do you want to help develop Dynamic languages on CLR? (
> http://members.microsoft.com/careers/search/details.aspx?JobID=6D4754DE-11F0-45DF-8B78-DC1B43134038
> )
>
> -----Original Message-----
> From: users-bounces at lists.ironpython.com [mailto:
> users-bounces at lists.ironpython.com] On Behalf Of Anthony Tarlano
> Sent: Thursday, March 16, 2006 11:45 PM
> To: Discussion of IronPython
> Subject: Re: [IronPython] Generator Performance (IronPython vs. CPython(
>
> Dino,
>
> Here is another performance example to provide more "food for thought".
>
> This is the second example from the article. In this example a
> comparison between a for loop and another generator based thread
> scheduler performing the same operations is made.
>
> Here is the code:
>
> # overhead.py
>
> import time
>
> TIMES = 100000
>
> threads = list()
>
> def stringops():
>     for n in xrange(TIMES):
>         s = "Mary had a little lamb"
>         s = s.upper()
>         s = "Mary had a little lamb"
>         s = s.lower()
>         s = "Mary had a little lamb"
>         s = s.replace('a','A')
>
> def scheduler():
>     for n in xrange(TIMES):
>         for thread in threads: thread.next()
>
> def upper():
>     while 1:
>         s = "Mary had a little lamb"
>         s = s.upper()
>         yield None
>
> def lower():
>     while 1:
>         s = "Mary had a little lamb"
>         s = s.lower()
>         yield None
>
> def replace():
>     while 1:
>         s = "Mary had a little lamb"
>         s = s.replace('a','A')
>         yield None
>
> if __name__=='__main__':
>     start = time.clock()
>     stringops()
>     looptime = time.clock()-start
>     print "LOOP TIME:", looptime
>
>     threads.append(upper())
>     threads.append(lower())
>     threads.append(replace())
>     start = time.clock()
>     scheduler()
>     threadtime = time.clock()-start
>     print "THREAD TIME:", threadtime
>
>
> And here are the pitiful results for IronPython vs CPython:
>
> sh-2.04$ python overhead.py
> LOOP TIME: 0.326167711259
> THREAD TIME: 0.548508818858
>
> sh-2.04$ IronPythonConsole overhead.py
> LOOP TIME: 0.734375
> THREAD TIME: 1.046875
>
> Anthony
>
> On 3/16/06, Dino Viehland <dinov at exchange.microsoft.com> wrote:
> > Thanks for the report of the perf issue.
> >
> > We are actually actively working on improving the perf of IronPython for
> the next release so I've gone ahead and filed a bug to make sure we look
> into this issue.  Hopefully we'll have something more concrete to let you
> know about this scenario soon, but unfortunately it's not one of the issues
> we've fixed so far.
> >
> >
> >
> > Do you want to help develop Dynamic languages on CLR? (
> http://members.microsoft.com/careers/search/details.aspx?JobID=6D4754DE-11F0-45DF-8B78-DC1B43134038
> )
> > -----Original Message-----
> > From: users-bounces at lists.ironpython.com [mailto:
> users-bounces at lists.ironpython.com] On Behalf Of Anthony Tarlano
> > Sent: Thursday, March 16, 2006 1:24 PM
> > To: Discussion of IronPython
> > Subject: [IronPython] Generator Performance (IronPython vs. CPython(
> >
> > Hi,
> >
> > I investigating the use of  lightweight threads, so I was reading
> > "Charming Python #b7: Implementing weightless threads with Python
> > generators. by David Mertz, Ph.D."
> >
> > The first example microthreads.py is about the simplest weightless
> > thread scheduler one could choose. Here is the code:
> >
> >
> -------------------------------------------------------------------------------------------------------------------
> > # microthreads.py
> >
> > import sys, time
> >
> > threads = []
> > TOTALSWITCHES = 10**6
> > NUMTHREADS    = 10**5
> >
> > def null_factory():
> >     def empty():
> >         while 1: yield None
> >     return empty()
> >
> > def quitter():
> >     for n in xrange(TOTALSWITCHES/NUMTHREADS):
> >         yield None
> >
> > def scheduler():
> >     global threads
> >     try:
> >         while 1:
> >             for thread in threads: thread.next()
> >     except StopIteration:
> >         pass
> >
> > if __name__ == "__main__":
> >     for i in range(NUMTHREADS):
> >         threads.append(null_factory())
> >     threads.append(quitter())
> >     starttime = time.clock()
> >     scheduler()
> >     print "TOTAL TIME:    ", time.clock()-starttime
> >     print "TOTAL SWITCHES:", TOTALSWITCHES
> >     print "TOTAL THREADS: ", NUMTHREADS
> >
> >
> -------------------------------------------------------------------------------------------------------------------
> >
> > After running the example on CPython the following results are printed:
> >
> > sh-2.04$ python microthreads.py
> > TOTAL TIME:     0.718205526121
> > TOTAL SWITCHES: 1000000
> > TOTAL THREADS:  100000
> >
> > After running the example on IronPython the following results are
> printed:
> >
> > sh-2.04$ IronPythonConsole microthreads.py
> > TOTAL TIME:     1.49999237061
> > TOTAL SWITCHES: 1000000
> > TOTAL THREADS:  100000
> >
> > This shows that IronPython took 0.781786844489 more then CPython to do
> > the same switching between generators in this example. I was quites
> > surprise to see this since that's more then double the time of
> > CPython.
> >
> > Thus, the question is whether this performance result is acceptable to
> > the IronPython team.
> >
> > Thanks,
> >
> > Anthony
> > _______________________________________________
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> >
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