+\documentclass{article}
+\usepackage[utf8]{inputenc}
+\usepackage{amsfonts,amssymb}
+\usepackage{amsmath}
+\usepackage{graphicx}
+
+\title{A scalable multisplitting algorithm for solving large sparse linear systems}
+
+
+
+\begin{document}
+\author{Raphaël Couturier \and Lilia Ziane Khodja}
+
+\maketitle
+
+
+\begin{abstract}
+In this paper we revist the krylov multisplitting algorithm presented in
+\cite{huang1993krylov} which uses a scalar method to minimize the krylov
+iterations computed by a multisplitting algorithm. Our new algorithm is simply a
+parallel multisplitting algorithm with few blocks of large size and a parallel
+krylov minimization is used to improve the convergence. Some large scale
+experiments with a 3D Poisson problem are presented. They show the obtained
+improvements compared to a classical GMRES both in terms of number of iterations
+and execution times.
+\end{abstract}
+
+\section{Introduction}
+
+Iterative methods are used to solve large sparse linear systems of equations of
+the form $Ax=b$ because they are easier to parallelize than direct ones. Many
+iterative methods have been proposed and adpated by many researchers. When
+solving large linear systems with many cores, iterative methods often suffer
+from scalability problems. This is due to their need for collective
+communications to perform matrix-vector products and reduction operations.
+
+\bibliographystyle{plain}
+\bibliography{biblio}
+
+\end{document}
