[pypy-commit] extradoc extradoc: tweaks to the introduction
bivab
noreply at buildbot.pypy.org
Thu Aug 16 13:39:08 CEST 2012
Author: David Schneider <david.schneider at picle.org>
Branch: extradoc
Changeset: r4607:98d5c1d806f3
Date: 2012-08-16 13:38 +0200
http://bitbucket.org/pypy/extradoc/changeset/98d5c1d806f3/
Log: tweaks to the introduction
diff --git a/talk/vmil2012/paper.tex b/talk/vmil2012/paper.tex
--- a/talk/vmil2012/paper.tex
+++ b/talk/vmil2012/paper.tex
@@ -153,22 +153,22 @@
of guards never fail at all, whereas those that do usually fail extremely
often.
-Besides being common, guards have various costs attached to them.
+Besides being common, guards have various costs associated to them.
Guards have a runtime cost, they take time to execute. Therefore it is
important to make the on-trace execution of guards as efficient as possible. On
the other hand, guards are possible deoptimization points. The recorded and
compiled path has to be left if a guard fails, returning control to the
interpreter. Therefore guards need enough associated information to enable
rebuilding the interpreter state. The memory overhead of this information
-should be kept low. These constraints and trade-offs are what make the design
+should be kept low. These constraints and trade-offs are what makes the design
and optimization of guards an important and non-trivial aspect of the construction
of a tracing just-in-time compiler.
%Section~\ref{sec:Evaluation} presents Figures about the absolute number of
%operations for each benchmark, and the overhead produced by the information
%stored at the different levels for the guards
-In this paper we want to substantiate the aforementioned observations and
-describe based on them the reasoning behind the implementation of guards in
+In this paper we want to substantiate the aforementioned observations about guards and
+describe based on them the reasoning behind their implementation in
RPython's tracing just-in-time compiler. the contributions of this paper are:
\begin{itemize}
\item an analysis and benchmark of guards in the context of RPython's tracing JIT,
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