deletions | additions       diff --git a/experim.tex b/experim.tex  index cbacdce..b1232e6 100644  --- a/experim.tex  +++ b/experim.tex 
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%TinyVM is thus an ideal playground to exercise our OSR technique, and we use it to run performance measurements on the shootout test suite, also known as the Computer Language Benchmark Game~\cite{shootout}.   %At the end of the section, we show experimental results for the case study presented in \mysection\ref{se:case-study}.  \begin{table} \begin{table}[b]  \begin{center}  \begin{small}  \begin{tabular}{ |c|c| } 
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%We generated the IR modules for our experiments with {\tt clang}, starting from the C version of the \shootout\ suite. In the version of the code we will refer to as {\em unoptimized}, no LLVM optimization passes were performed on the code other than {\em mem2reg}, which promotes memory references to register references and constructs the SSA (Static Single Assignment) form. Starting from this version, we then generate an {\em optimized} version performing using the LLVM IR optimizer {\tt opt} at {\tt -O1} optimization level.  We generated generate  the IR modules for our experiments with {\tt clang} starting from the C version of the \shootout\ suite. In the version of the code we will refer to as {\em unoptimized}, the only LLVM optimization pass we performed perform  is {\tt mem2reg}, which promotes memory stack  references to register references registers  and constructs the SSA form. \ifdefined \fullver  Starting from this version, we also generate an {\em optimized} versionperforming  using the LLVM IR optimizer {\tt opt} at {\tt -O1} optimization level. \else  Starting from this version, we also generate an {\em optimized} versionperforming  using the LLVM optimizer {\tt opt -O1}. \fi  For question Q4, we analyze the impact of the optimization technique presented in \mysection\ref{sse:optimizing_feval} on the running time of a few numeric benchmarks, namely {\tt odeEuler}, {\tt odeMidpt}, {\tt odeRK4}, and {\tt sim\_anl}. The first three benchmarks solve an ODE for heat treating simulation using the Euler, midpoint, and Range-Kutta method, respectively\footnote{\url{http://web.cecs.pdx.edu/~gerry/nmm/mfiles/}}; the last benchmark minimizes the six-hump camelback function with the method of simulated annealing\footnote{\url{http://www.mathworks.com/matlabcentral/fileexchange/33109-simulated-annealing-optimization}}.