The present paper is organized as follows. In Section~\ref{sec:02} some related
works are presented. Section~\ref{sec:03} presents our two-stage algorithm using
-a least-square residual minimization. Section~\ref{sec:04} describes some
-convergence results on this method.
- Section~\ref{sec:05} shows some
+a least-square residual minimization. Section~\ref{sec:04} describes some
+convergence results on this method. Section~\ref{sec:05} shows some
experimental results obtained on large clusters of our algorithm using routines
-of PETSc toolkit.
+of PETSc toolkit. Finally Section~\ref{sec:06} concludes and gives some
+perspectives.
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characteristics. For all the matrices, the name, the field, the number of rows
and the number of nonzero elements is given.
-\begin{table}
+\begin{table*}
\begin{center}
\begin{tabular}{|c|c|r|r|r|}
\hline
\caption{Main characteristics of the sparse matrices chosen from the Davis collection}
\label{tab:01}
\end{center}
-\end{table}
+\end{table*}
The following parameters have been chosen for our experiments. As by default
the restart of GMRES is performed every 30 iterations, we have chosen to stop
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\section{Conclusion}
-\label{sec:05}
+\label{sec:06}
%The conclusion goes here. this is more of the conclusion
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