X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/64524506d883bc0ba97cb6a424cb576cdb8e4262..774b7cd45da63cb7d2c5b2b57a5f7cb775344a59:/hpcc.tex?ds=sidebyside

diff --git a/hpcc.tex b/hpcc.tex
index e06c9c5..dd06eeb 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -202,7 +202,7 @@ iterations and so to very different execution times.
 
 \section{SimGrid}
 
-SimGrid~\cite{casanova+legrand+quinson.2008.simgrid,SimGrid} is a simulation
+SimGrid~\cite{SimGrid,casanova+legrand+quinson.2008.simgrid} is a simulation
 framework to study the behavior of large-scale distributed systems.  As its name
 says, it emanates from the grid computing community, but is nowadays used to
 study grids, clouds, HPC or peer-to-peer systems.  The early versions of SimGrid
@@ -372,13 +372,20 @@ Table~\ref{tab.cluster.2x50} with a matrix size ranging from $N_x = N_y = N_z =
 62 \text{ to } 171$ elements or from $62^{3} = \np{238328}$ to $171^{3} =
 \np{5211000}$ entries.
 
+% use the same column width for the following three tables
+\newlength{\mytablew}\settowidth{\mytablew}{\footnotesize\np{E-11}}
+\newenvironment{mytable}[1]{% #1: number of columns for data
+  \renewcommand{\arraystretch}{1.3}%
+  \begin{tabular}{|>{\bfseries}r%
+                  |*{#1}{>{\centering\arraybackslash}p{\mytablew}|}}}{%
+    \end{tabular}}
+
 \begin{table}[!t]
   \centering
   \caption{$2$ clusters, each with $50$ nodes}
   \label{tab.cluster.2x50}
-  \renewcommand{\arraystretch}{1.3}
 
-  \begin{tabular}{|>{\bfseries}r|*{12}{c|}}
+  \begin{mytable}{6}
     \hline
     bw
     & 5         & 5         & 5         & 5         & 5         & 50 \\
@@ -398,11 +405,11 @@ Table~\ref{tab.cluster.2x50} with a matrix size ranging from $N_x = N_y = N_z =
     speedup
     & 0.396     & 0.392     & 0.396     & 0.391     & 0.393     & 0.395 \\
     \hline
-  \end{tabular}
+  \end{mytable}
 
   \smallskip
 
-  \begin{tabular}{|>{\bfseries}r|*{12}{c|}}
+  \begin{mytable}{6}
     \hline
     bw
     & 50        & 50        & 50        & 50        & 10        & 10 \\
@@ -422,7 +429,7 @@ Table~\ref{tab.cluster.2x50} with a matrix size ranging from $N_x = N_y = N_z =
     speedup
     & 0.398     & 0.388     & 0.393     & 0.394     & 0.63      & 0.778 \\
     \hline
-  \end{tabular}
+  \end{mytable}
 \end{table}
   
 Then we have changed the network configuration using three clusters containing
@@ -435,9 +442,8 @@ speedups less than $1$ with a matrix size from $62$ to $100$ elements.
   \centering
   \caption{$3$ clusters, each with $33$ nodes}
   \label{tab.cluster.3x33}
-  \renewcommand{\arraystretch}{1.3}
 
-  \begin{tabular}{|>{\bfseries}r|*{6}{c|}}
+  \begin{mytable}{6}
     \hline
     bw
     & 10       & 5        & 4        & 3        & 2        & 6 \\
@@ -457,10 +463,9 @@ speedups less than $1$ with a matrix size from $62$ to $100$ elements.
     speedup
     & 0.997    & 0.99     & 0.93     & 0.84     & 0.78     & 0.99 \\
     \hline
-  \end{tabular}
+  \end{mytable}
 \end{table}
 
-
 In a final step, results of an execution attempt to scale up the three clustered
 configuration but increasing by two hundreds hosts has been recorded in
 Table~\ref{tab.cluster.3x67}.
@@ -469,9 +474,8 @@ Table~\ref{tab.cluster.3x67}.
   \centering
   \caption{3 clusters, each with 66 nodes}
   \label{tab.cluster.3x67}
-  \renewcommand{\arraystretch}{1.3}
 
-  \begin{tabular}{|>{\bfseries}r|c|}
+  \begin{mytable}{1}
     \hline
     bw         & 1 \\
     \hline
@@ -485,7 +489,7 @@ Table~\ref{tab.cluster.3x67}.
     \hline
     speedup    & 0.9 \\
     \hline
- \end{tabular}
+ \end{mytable}
 \end{table}
 
 Note that the program was run with the following parameters:
