Python patch to speed things up to 20%

http://bugs.python.org/issue4753

by vaksel • 18 years ago

67 22 18 years ago

bugs.python.org

SirWart• 18 years ago

The best explanation for how the optimization works is actually in the patch itself: http://bugs.python.org/file12524/threadedceval5.patch.

cool-RR• 18 years ago

Are these the 20% we lost with Python 3?

neilc• 18 years ago

Not the "same" 20%, no: the same optimization could be applied to Python 2.x, presumably yielding a comparable relative speedup.

listic2• 18 years ago

I saw this technique, namely using gcc's labels-as-values extension to efficiently implement threaded code, in gForth. The developers of gForth originally chose gcc back in 1992 because it had such a neat feature that allowed to implement threaded code efficiently. Unfortunately for gForth, somewhere along the way gcc developers changed something and gForth took massive perfomance hit (2 or 3 times slowdown) gForth developers tried to negotiate with gcc team, but they didn't seem to be interested to do additional work seemingly needed only for one application (gForth). The gForth developers couldn't afford to fork gcc either (gcc is too big; too much work)

I guess the moral of the story should be: beware of such speedups that come from nonstandard technology you cannot control.

The whole story is from my memory, as I cannot find the source right now.

anewaccountname• 18 years ago

seems like a candidate for inline assembly.

listic2• 18 years ago

sure, but what if you might not want to use inline assembly i.e. for easier portability across platforms. Forths before used it all the way, but gForth didn't want to.

amix3• 18 years ago

While I really love Python as the language I really hate its primitive implementation. 20% is nothing compared to what would be gained if Python ran on a virtual machine that was JIT'ed.

Java for example got a 10 to 20 times performance gain from moving to HotSpot (their JIT'ed VM). And similar gain's have been seen in Chrome's V8 JavaScript VM or Strongtalk.

Anyway, it's kind of sad that such a great language has such a braindead implementation :-(

And unfortunately, the same thing can be said about Ruby as well.

jd4• 18 years ago

Python's implementation is focused on code readability. One of Guido's initial goals was that no matter how insane the input, the interpreter must never crash. His emphasis on simple and clear code (and an intuitive bytecode) gets in the way of performance.

The Ruby interpreter is quite terrible, but a lot of people are trying to make it better. Give it a couple of years.

Also, you imply that both implementations are really naive. They're not. With languages such as Python and Ruby there is much less to gain with JIT compilation than with Java. Suppose you have this Python program:

    def trivial(a, b):
        return a + b

What can the JIT optimize? The function call? Not always, because the function can be redefined during runtime (unlike with Java and .NET). Can the function be inlined? No. Can the function call frame be stack-allocated? Well, maybe, at a significant complexity cost: most scopes in Python are essentially closures so you have to treat carefully there too (upward funarg problems). Obviously the "+" function call can't be optimized much, because you don't know the types of "a" and "b". And even if you did it wouldn't help much.

Not done yet!

Even IF you optimize everything using the NBOCK (Non Braindead Omniscient Compiler Kit). Now you know that you're dealing with integers, and you know where the function is defined, and you know the function's definition is not going to change, and you know all function arguments can be declared locally and you know only integers will be passed to and returned from the function. Can you now transform it into a few MOV instructions? Alas, no.

Maybe the integers will overflow. And if they overflow you either want to throw an exception or allocate additional space and transform the integer to a heap-allocated large integer. (And you have to do all the necessary cache invalidation.)

So even if you are omniscient there is no low-hanging fruit. In the end even the logic of adding two integers is sufficiently complex that it warrants its own C function and inclining becomes only marginally useful.

When you take mundane issues such as maintainability, flexibility, and portability into account there are very few reasons left for building a JIT compiler for Python. Note that all these optimizations are viable (to an extent) with languages such as Haskell, C# and Java.

marcher• 18 years ago

The PyPy folks are working on a JIT, apparently with great speedups. They've been detailing their work on their blog: http://morepypy.blogspot.com/

Also, are JavaScript and Python really that dissimilar? Everyone's working on tracing JITs for JavaScript now, with great results.

gruseom2• 18 years ago

You seem to imply that they're viable because those languages aren't as dynamic as Python. Yet Smalltalk and Lisp (edit: and Javascript) are at least this dynamic, and have implementations that go far beyond this. In fact Java's (edit: and V8's) JIT technology came from the Smalltalk world.

nailer• 18 years ago

Thanks jd - I found out a few months ago that Python JITs weren't as fast as Java JITs, but had never quite grasped that there was solid reason why.

tocomment2• 18 years ago

You sound pretty knowledgeable on this stuff. Maybe use your smarts to offer solutions too? :-)

Python patch to speed things up to 20%

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