[pypy-svn] r63801 - pypy/extradoc/talk/icooolps2009-dotnet

antocuni at codespeak.net antocuni at codespeak.net
Tue Apr 7 17:29:23 CEST 2009

Author: antocuni
Date: Tue Apr  7 17:29:20 2009
New Revision: 63801

fix last davide's comment

Modified: pypy/extradoc/talk/icooolps2009-dotnet/conclusion.tex
--- pypy/extradoc/talk/icooolps2009-dotnet/conclusion.tex	(original)
+++ pypy/extradoc/talk/icooolps2009-dotnet/conclusion.tex	Tue Apr  7 17:29:20 2009
@@ -50,8 +50,6 @@
 about the differences between PyPy and IronPython apply to all DLR based
-\anto{XXX: please review the last two paragraphs}
 \section{Conclusion and Future Work}
 In this paper we gave an overview of PyPy's JIT compiler generator,

Modified: pypy/extradoc/talk/icooolps2009-dotnet/intro.tex
--- pypy/extradoc/talk/icooolps2009-dotnet/intro.tex	(original)
+++ pypy/extradoc/talk/icooolps2009-dotnet/intro.tex	Tue Apr  7 17:29:20 2009
@@ -76,10 +76,9 @@
 The main difference between the JIT compilers generated by PyPy and the
 ones found in other projects like IronPython is that the latter compile
-code at the method granularity: if on the one hand they can exploit
-some of the knowledge gathered at runtime \davide{this contradicts what is stated in the intro} (e.g.\ the types of method
-parameters), on the other hand they can do little to optimize most of
+code at the method granularity: they can do little to optimize most of
 the operations inside, because few assumptions can be made about the
+types of the arguments and the
 global state of the program.  The PyPy JITs, on the other hand, work at
 a sub-method granularity, as described next.

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