modif

diff --git a/Revision.tex b/Revision.tex
index 4b4ffe3c1cdd02f37aee38d248aece0b1936bc5a..0ccf1a3d245ddd2dcac2ee88f523a6bd58ef362e 100644 (file)
--- a/Revision.tex
+++ b/Revision.tex
@@ -85,6 +85,6 @@ Section 4 has been rewritten in order to explain our choice to compare our Krylo
 \item ``Was the method of reference [9] implemented by the authors of [9]? How did they do against GMRES?''
 
 \medskip
 \item ``Was the method of reference [9] implemented by the authors of [9]? How did they do against GMRES?''
 
 \medskip

-As explained in the paper, authors of [9] have not implemented the method of reference [9]. They have mainly focused on the convergence analysis of various forms of the algorithm [9] and presented results of numerical examples on a sequential computer. 
+As explained in the paper, authors of [9] have not implemented the method of reference [9]. They have mainly focused on the convergence analysis of various forms of the algorithm [9] and presented simulations of numerical examples on a sequential computer. 

 \end{enumerate}
 \end{document} 
 \end{enumerate}
 \end{document} 

diff --git a/krylov_multi_reviewed.tex b/krylov_multi_reviewed.tex
index 13341729f3ecf6e0745187fba72aeae51cd9318d..0ad524f6eb4470065a52a34ffd8bed2deadd4443 100644 (file)
--- a/krylov_multi_reviewed.tex
+++ b/krylov_multi_reviewed.tex
@@ -367,7 +367,8 @@ We have performed some experiments on an infiniband cluster of three Intel Xeon
 \label{fig:002}
 \end{figure}
 
 \label{fig:002}
 \end{figure}
 

-The experiments are performed on 3 different clusters of cores interconnected by an infiniband network (each cluster is a quad-core CPU). Figures~\ref{fig:001} and~\ref{fig:002} show the scalability performances of GMRES, classical multisplitting and Krylov multisplitting methods: strong and weak scaling are presented respectively. We can remark from these figures that the performances of our Krylov multisplitting method are better than those of GMRES and classical multisplitting methods. In the experiments conducted in this work, our method is about twice faster than the GMRES method and about 9 times faster than the classical multisplitting method. Our multisplitting method uses a minimization step over a Krylov subspace which reduces the number of iterations and accelerates the convergence. We can also remark that the performances of the classical block Jacobi multisplitting method are the worst compared with those of the other two methods. This is why in the following experiments we compare the performances of our Krylov multisplitting method with only those of the GMRES method.
+%%The experiments are performed on 3 different clusters of cores interconnected by an infiniband network (each cluster is a quad-core CPU). 
+Figures~\ref{fig:001} and~\ref{fig:002} show the scalability performances of GMRES, classical multisplitting and Krylov multisplitting methods: strong and weak scaling are presented respectively. We can remark from these figures that the performances of our Krylov multisplitting method are better than those of GMRES and classical multisplitting methods. In the experiments conducted in this work, our method is about twice faster than the GMRES method and about 9 times faster than the classical multisplitting method. Our multisplitting method uses a minimization step over a Krylov subspace which reduces the number of iterations and accelerates the convergence. We can also remark that the performances of the classical block Jacobi multisplitting method are the worst compared with those of the other two methods. This is why in the following experiments we compare the performances of our Krylov multisplitting method with only those of the GMRES method.

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