pedronis at codespeak.net pedronis at codespeak.net
Wed May 31 15:28:10 CEST 2006

Author: pedronis
Date: Wed May 31 15:28:09 2006
New Revision: 27983

Modified:
Log:
dhrystone 2.0

take care of last XXX

==============================================================================
+++ pypy/extradoc/talk/dls2006/paper.tex	Wed May 31 15:28:09 2006
@@ -308,13 +308,15 @@
\label{fig_llappend}
\end{figure}

-In the example of the \texttt{malloc} operation, replaced by a call to GC
-code, this GC code can invoke a complete collection of dead objects, and
-can thus be arbitrarily complicated.  Still, our GC code is entirely
-written in plain Python, and it manipulates "objects" that are still at
-a lower level: pointer and address objects.  Even with the restriction
-of having to use pointer-like and address-like objects, Python remains
-more expressive than, say, C to write a GC.  [XXX see also Jikes]
+In the example of the \texttt{malloc} operation, replaced by a call to
+GC code, this GC code can invoke a complete collection of dead
+objects, and can thus be arbitrarily complicated.  Still, our GC code
+is entirely written in plain Python, and it manipulates "objects" that
+are still at a lower level: pointer and address objects.  Even with
+the restriction of having to use pointer-like and address-like
+objects, Python remains more expressive than, say, C to write a GC
+(Jikes RVM's GC work \cite{JikesGC} was the inspiration to try to
+express GCs in Python, see \ref{relatedwork}).

In the sequel, we will call \textit{system code} functions written in
Python that are meant to be analysed by the front-end.  For the
@@ -910,7 +912,7 @@

The tool-chain has been tested with and can sucessfully apply
transformations enabling various combinations of features. The
-translated interpreters are benchmarked using pystone (a [Dhrystone]
+translated interpreters are benchmarked using pystone (a [Dhrystone] 2.0
derivative traditionally used by the Python community, although it is
a rather poor benchmark) and the classical [Richards] benchmark and
compared against [CPython] 2.4.3 results and are summarized in table