\item maximum number of inner and outer iterations;
\item inner and outer precisions;
\item matrix size (N$_{x}$, N$_{y}$ and N$_{z}$);
- \item matrix diagonal value = 6.0 (for synchronous Krylov multisplitting experiments and 6.2 for asynchronous block Jacobi experiments); \RC{CE tu vérifie, je dis ca de tête}
+ \item matrix diagonal value = 6.0 (for synchronous Krylov multisplitting experiments and 6.2 for asynchronous block Jacobi experiments); \RC{CE tu vérifies, je dis ca de tête}
\item execution mode: synchronous or asynchronous.
\end{itemize}
\section{Experimental Results}
\label{sec:expe}
+In this section, experiments for both Multisplitting algorithms are reported. First the problem sued in our experiments is described.
+
+\RC{Lilia a toi de jouer}
\subsection{Study setup and Simulation Methodology}
-To conduct our study, we have put in place the following methodology
-which can be reused for any grid-enabled applications.
+First, to conduct our study, we propose the following methodology
+which can be reused for any grid-enabled applications.\\
\textbf{Step 1} : Choose with the end users the class of algorithms or
the application to be tested. Numerical parallel iterative algorithms
\textbf{Step 2} : Collect the software materials needed for the
experimentation. In our case, we have two variants algorithms for the
resolution of the 3D-Poisson problem: (1) using the classical GMRES (Algo-1); (2) and the multisplitting method (Algo-2). In addition, Simgrid simulator has been chosen to simulate the behaviors of the
-distributed applications. Simgrid is running on the Mesocentre datacenter in Franche-Comte University but also in a virtual machine on a laptop. \\
+distributed applications. Simgrid is running on the Mesocentre datacenter in the University of Franche-Comte and also in a virtual machine on a laptop. \\
\textbf{Step 3} : Fix the criteria which will be used for the future
results comparison and analysis. In the scope of this study, we retain
