PyPy 1.4: Ouroboros in practice

#1

Post by aaw » Fri, Nov 26, 2010, 6:25 PM UTC

PyPy 1.4: Ouroboros in practice
morepypy.blogspot.com

Re: PyPy 1.4: Ouroboros in practice

#2

Post by orangecat » Fri, Nov 26, 2010, 7:49 PM UTC

Interesting and promising. PyPy 1.4:

    >>>> t1 = time.time(); a=[x*x for x in xrange(1000000)]; time.time()-t1
    0.38609600067138672
    >>>> t1 = time.time(); a=[x*x+math.sin(x/1000000.) for x in xrange(1000000)]; time.time()-t1
    0.42182803153991699

Python 2.7:

    >>> t1 = time.time(); a=[x*x for x in xrange(1000000)]; time.time()-t1
    0.25005197525024414
    >>> t1 = time.time(); a=[x*x+math.sin(x/1000000.) for x in xrange(1000000)]; time.time()-t1
    0.6075689792633057

Both running in 64-bit on a 2.53GHz Core 2 Duo. It looks like PyPy's JIT has some fixed overhead, but can heavily optimize operations once it gets going.

Re: PyPy 1.4: Ouroboros in practice

#3

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Re: PyPy 1.4: Ouroboros in practice

#4

Post by dochtman » Fri, Nov 26, 2010, 8:11 PM UTC

I think this is the first PyPy release that's actually viable to use for me (because of x86-64). Very exciting!

(Hope they catch up with 2.6 - or 2.7 - soon, though.)

Re: PyPy 1.4: Ouroboros in practice

#5

Post by kingkilr » Fri, Nov 26, 2010, 8:12 PM UTC

dochtman wrote: post #4

I think this is the first PyPy release that's actually viable to use for me (because of x86-64). Very exciting! (Hope they catch up with 2.6 - or 2.7 - soon, though.)

We have a fast-forward branch that is currently working on moving to Python 2.7.

Re: PyPy 1.4: Ouroboros in practice

#6

Post by dochtman » Fri, Nov 26, 2010, 8:42 PM UTC

kingkilr wrote: post #5

dochtman wrote: post #4

I think this is the first PyPy release that's actually viable to use for me (because of x86-64). Very exciting! (Hope they catch up with 2.6 - or 2.7 - soon, though.)

We have a fast-forward branch that is currently working on moving to Python 2.7.

I know, I hope its merging is followed by a quick release. :)

Re: PyPy 1.4: Ouroboros in practice

#7

Post by carlosedp » Fri, Nov 26, 2010, 11:19 PM UTC

I hope they add support for JIT with the Stackless features.

Re: PyPy 1.4: Ouroboros in practice

#8

Post by RyanMcGreal » Fri, Nov 26, 2010, 11:36 PM UTC

>PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython.

What still works in CPython but not PyPy?

Re: PyPy 1.4: Ouroboros in practice

#9

Post by cool-RR » Fri, Nov 26, 2010, 11:56 PM UTC

RyanMcGreal wrote: post #8

>PyPy is a very compliant Python interpreter, almost a drop-in replacement for CPython. What still works in CPython but not PyPy?

wxPython is something I personally miss.

Re: PyPy 1.4: Ouroboros in practice

#10

Post by timtadh » Sat, Nov 27, 2010, 12:03 AM UTC

Currently testing a CPU intensive algorithm I need for my current research project. Hoping it will save me some time. When I am done I will post the results!

[Edit:]

Pretty good so far!

    ~/stuff/Programming/faultire/src/
    hendersont@glycineportable src $ time pypy sleepytree/test_metricspace.py 
    .......
    ----------------------------------------------------------------------
    Ran 7 tests in 39.621s

    OK

    real    0m39.675s
    user    0m39.150s
    sys     0m0.170s
    ~/stuff/Programming/faultire/src/
    hendersont@glycineportable src $ time python sleepytree/test_metricspace.py 
    .......
    ----------------------------------------------------------------------
    Ran 7 tests in 69.442s

    OK

    real    1m9.483s
    user    1m8.970s
    sys     0m0.110s