[pypy-svn] r8011 - pypy/trunk/doc
lac at codespeak.net
lac at codespeak.net
Thu Dec 30 19:35:39 CET 2004
Date: Thu Dec 30 19:35:34 2004
New Revision: 8011
Ok, made it a doc so that other people can edit as well. Remember it is
an email reply, and don't worry about formatting gorp that makes it look
stupid on the website. If we want to make a website version, we can
do that then.
--- (empty file)
+++ pypy/trunk/doc/to_edu_sig.txt Thu Dec 30 19:35:34 2004
@@ -0,0 +1,79 @@
+Happy New Year, Dethe! Thank you for your interest. You write:
+>PyPy uses a similar approach to Pyrex, called Psyco, which compiles
+>directly to 80x86 machine code (Pyrex compiles to cross-platform C
+>code). This allows PyPy to attempt to be faster than C-Python by
+>creating compiler optimizations. Not sure what the PyPy story is for
+>non-x86 platforms. There is also a project to recreate Python on top
+>of Smalltalk, by L. Peter Deutch, which he expects to be faster than
+>C-Python (and if anyone can do it, he could).
+>Nice to see y'all again. Happy New Year (or Gnu Year?).
+I'd like to clarify a few misunderstandings I think you have. Psyco
+is not a technique, but rather a specialising compiler available as a
+Python extension module. It compiles directly to 386 machine
+code. PyPy, on the other hand, currently emits C code. Our previous
+version emitted Pyrex code. Some people in Korea are making a version
+that emits Lisp code. PyPy doesn't use Psyco, though many ideas are
+common to both.
+What's more there is nothing magic about machine code that makes it
+automatically fast -- an inefficiently-coded algorithm in assembler is
+still a turtle. The win in using PyPy is not about 'saving the time
+it takes to have a conversation with your C compiler', but instead
+about making such conversations more productive and useful. The more
+information you can tell your C compiler about your data, the better
+code it is prepared to generate. This is the tradeoff between
+flexibility and speed.
+When your Python system sees x = a + b it has no clue as to what types
+a and b are. They could be anything. This 'being ready to handle
+everything' has a large performance penalty. The runtime system has
+to do be prepared to do a _lot_, so it has to be fairly intelligent.
+All this intelligence is in the form of code instructions, and there
+are a lot of them that the runtime system has to execute, every time
+it wants to do anything at all. On the other hand, at code _reading_
+time, the Python interpreter is purposefully stupid-but-straightforward.
+It doesn't have much to do, and so can be relatively quick about not doing it.
+A statically-typed compiled language works in precisely the other way.
+When the runtime system of a statically typed language sees x = a + b,
+it already knows all about x, a and b and their types. All the hard
+work was done in the compiling phase. There is very little left to
+worry about -- you might get an overflow exception or something -- but
+as an oversimplification, all the runtime system of a statically typed
+langauge has to know how to do is how to load and run. That's fast.
+So, one way you could speed up Python is to add type declarations,
+thus simplifying the life of the runtime system. This proposed
+solution is more than a little drastic for those of us who like duck
+typing, signature based polymorphism, and the particular way coding in
+Python makes you think and feel.
+The PyPy alternative is to make the interpreter even smarter, and a
+whole lot better at remembering what it is doing. For instance, when
+it sees x = a + b instead of just adding this particular int to this
+particular int, it could generate some general purpose code for adding
+ints to ints. This code could be thus used for all ints that you wish
+to add this way. So while the first time is slow, the _next_ time
+will be a lot faster. And that is where the performance speedup
+happens -- in code where the same lines get run again, and again, and
+again. If all you have is a mainline where each line of code gets
+executed once, then we won't help you at all.
+Psyco is about as far as you can get with this approach and be left
+with a module you can import and use with regular python 2.2 or
+better. See: http://psyco.sourceforge.net/ PyPy is what you get when
+you pitch the old interpreter and write your own. See:
+And we should probably move further disussion to pypy-dev, here:
+Thanks for your interest, and thanks for writing,
+Laura Creighton (for PyPy)
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