X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/645f3921415c716f3c2185090bd32a5d48861879..69c9882b87d766e94a292ccab6964bcd7f8b23c6:/hpcc.tex

diff --git a/hpcc.tex b/hpcc.tex
index 1179edb..9dbbb3f 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -259,7 +259,7 @@ their bandwidth and latency, and the routing strategy.  The simulated running
 time of the application is computed according to these properties.
 
 To compute the durations of the operations in the simulated world, and to take
-into account resource sharing (e.g.  bandwith sharing between competiting
+into account resource sharing (e.g. bandwidth sharing between competing
 communications), SimGrid uses a fluid model.  This allows to run relatively fast
 simulations, while still keeping accurate
 results~\cite{bedaride:hal-00919507,tomacs13}.  Moreover, depending on the
@@ -447,7 +447,7 @@ containing 50 hosts each, totaling 100 hosts. Various combinations of the above
 factors have providing the results shown in Table~\ref{tab.cluster.2x50} with a
 matrix size ranging from $N_x = N_y = N_z = \text{62}$ to 171 elements or from
 $\text{62}^\text{3} = \text{\np{238328}}$ to $\text{171}^\text{3} =
-\text{\np{5211000}}$ entries.
+\text{\np{5000211}}$ entries.
 
 % use the same column width for the following three tables
 \newlength{\mytablew}\settowidth{\mytablew}{\footnotesize\np{E-11}}
@@ -538,7 +538,7 @@ relative gains greater than 1 with a matrix size from 62 to 100 elements.
     & \np{E-5} & \np{E-5} & \np{E-5} & \np{E-5} & \np{E-5} & \np{E-5} \\
     \hline
     Relative gain
-    & 1.003    & 1,01     & 1,08     & 0.19     & 1.28     & 1.01 \\
+    & 1.003    & 1.01     & 1.08     & 1.19     & 1.28     & 1.01 \\
     \hline
   \end{mytable}
 \end{table}
@@ -588,11 +588,8 @@ lat latency, \dots{}).
 	\item Maximum number of internal and external iterations;
 	\item Internal and external precisions;
 	\item Matrix size $N_x$, $N_y$ and $N_z$;
-%<<<<<<< HEAD
 	\item Matrix diagonal value: \np{6.0};
 	\item Matrix Off-diagonal value: \np{-1.0};
-%=======
-%>>>>>>> 5fb6769d88c1720b6480a28521119ef010462fa6
 	\item Execution Mode: synchronous or asynchronous.
 \end{itemize}
 
@@ -634,6 +631,8 @@ Table~\ref{tab.cluster.3x67}.
 \LZK{Dans le papier, on compare les deux versions synchrone et asycnhrone du multisplitting. Y a t il des résultats pour comparer gmres parallèle classique avec multisplitting asynchrone? Ca permettra de montrer l'intérêt du multisplitting asynchrone sur des clusters distants}
 \CER{En fait, les résultats ont été obtenus en comparant les temps d'exécution entre l'algo classique GMRES en mode synchrone avec le multisplitting en mode asynchrone, le tout sur un environnement de clusters distants}
 
+\RC{Est ce qu'on sait expliquer pourquoi il y a une telle différence entre les résultats avec 2 et 3 clusters... Avec 3 clusters, ils sont pas très bons... Je me demande s'il ne faut pas les enlever...}
+
 \section{Conclusion}
 The experimental results on executing a parallel iterative algorithm in 
 asynchronous mode on an environment simulating a large scale of virtual