Traditional parallel iterative solvers are based on fine-grain computations that
frequently require data exchanges between computing nodes and have global
-synchronizations that penalize the scalability. Particularly, they are more
-penalized on large scale architectures or on distributed platforms composed of
-distant clusters interconnected by a high-latency network. It is therefore
-imperative to develop coarse-grain based algorithms to reduce the communications
-in the parallel iterative solvers. Two possible solutions consists either in
-using asynchronous iterative methods~\cite{ref18} or in using multisplitting
-algorithms. In this paper, we will reconsider the use of a multisplitting
-method. In opposition to traditional multisplitting method that suffer from slow
-convergence, as proposed in~\cite{huang1993krylov}, the use of a minimization
-process can drastically improve the convergence.\\
+synchronizations that penalize the scalability~\cite{zkcgb+14:ij}. Particularly,
+they are more penalized on large scale architectures or on distributed platforms
+composed of distant clusters interconnected by a high-latency network. It is
+therefore imperative to develop coarse-grain based algorithms to reduce the
+communications in the parallel iterative solvers. Two possible solutions
+consists either in using asynchronous iterative methods~\cite{ref18} or in using
+multisplitting algorithms. In this paper, we will reconsider the use of a
+multisplitting method. In opposition to traditional multisplitting method that
+suffer from slow convergence, as proposed in~\cite{huang1993krylov}, the use of
+a minimization process can drastically improve the convergence.\\
%%% AJOUTE************************
\begin{figure}[htbp]
\centering
\begin{tabular}{c}
-\includegraphics[width=0.8\textwidth]{weak_scaling_280k} \\ \includegraphics[width=0.8\textwidth]{weak_scaling_280K}\\
+\includegraphics[width=0.8\textwidth]{weak_scaling_280k} \\ \includegraphics[width=0.8\textwidth]{weak_scaling_280K2}\\
\end{tabular}
\caption{Weak scaling with 3 blocks of 4 cores each to solve a 3D Poisson problem with approximately 280K components per core}
\label{fig:002}
\begin{figure}[htbp]
\centering
\includegraphics[width=0.7\textwidth]{nb_iter_sec}
-\caption{Number of iterations per second with the same parameters as in Table~\ref{tab1} (weak scaling) with only 2 blocks of cores}
+\caption{Number of iterations per second with the same parameters as in Table~\ref{tab1} (weak scaling) with only blocks of cores}
\label{fig:01}
\end{figure}
