3 ms·

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 virtua

by amix 18y 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.

jd 18y 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 18y 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/ http://morepypy.blogspot.com/ Also, are JavaScript and Python really that dissimilar? Everyone's working on tracing JITs for JavaScript now, with great results.
  - jmtulloss 18y ago
    My impression is that Python's interpreter is pretty good, so it wouldn't benefit as much from JITing. That being said, it would certainly help, and the same library used in TraceMonkey (nanojit) could probably be used in Python.
  - jd 18y ago
    Take a look at the PyPy FAQ. They're using annotations, type inference assumptions, and so on. PyPy seems to be focused on a Jit-able subset of Python. It's not a project that can one day be transparently included in the new Python release. JavaScript and Python are not that dissimilar. So we see similar results with JavaScript. People want performance, so a lot of projects are started where people attempt to JIT JavaScript - but in the 14 or so years of JS's existence JavaScript is still several orders of magnitude slower than less dynamic languages. Java and C# have never been as slow as JavaScript is today. Will JIT-ing JavaScript help? Sure. But -great- results? I wouldn't go that far.
    - jey 18y ago
      No, PyPy is a full Python implementation that uses program analysis to identify and JIT the JITable parts of the code. The FAQ says that PyPy is a drop-in replacement for CPython unless you depend on a CPython extension module. http://codespeak.net/pypy/dist/pypy/doc/faq.html#is-pypy-a-drop-in-replacement-for-cpython http://codespeak.net/pypy/dist/pypy/doc/faq.html#is-pypy-a-d...
      - jd 18y ago
        The drop in replacement is slower than CPython. Likely to change in the future, but still.

by amix 18y ago

jd 18y 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 18y 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/ http://morepypy.blogspot.com/ Also, are JavaScript and Python really that dissimilar? Everyone's working on tracing JITs for JavaScript now, with great results.
- jmtulloss 18y ago
  My impression is that Python's interpreter is pretty good, so it wouldn't benefit as much from JITing. That being said, it would certainly help, and the same library used in TraceMonkey (nanojit) could probably be used in Python.
- jd 18y ago
  Take a look at the PyPy FAQ. They're using annotations, type inference assumptions, and so on. PyPy seems to be focused on a Jit-able subset of Python. It's not a project that can one day be transparently included in the new Python release. JavaScript and Python are not that dissimilar. So we see similar results with JavaScript. People want performance, so a lot of projects are started where people attempt to JIT JavaScript - but in the 14 or so years of JS's existence JavaScript is still several orders of magnitude slower than less dynamic languages. Java and C# have never been as slow as JavaScript is today. Will JIT-ing JavaScript help? Sure. But -great- results? I wouldn't go that far.
  - jey 18y ago
    No, PyPy is a full Python implementation that uses program analysis to identify and JIT the JITable parts of the code. The FAQ says that PyPy is a drop-in replacement for CPython unless you depend on a CPython extension module. http://codespeak.net/pypy/dist/pypy/doc/faq.html#is-pypy-a-drop-in-replacement-for-cpython http://codespeak.net/pypy/dist/pypy/doc/faq.html#is-pypy-a-d...
    - jd 18y ago
      The drop in replacement is slower than CPython. Likely to change in the future, but still.