petites modifs

diff --git a/biblio.bib b/biblio.bib
index ecc1622d49ec48977fb27982cb1d65c17c5b6833..c3ab7d418df69f9171b283450db05dff5e3fb1ce 100644 (file)
--- a/biblio.bib
+++ b/biblio.bib
@@ -206,3 +206,18 @@ year = {1994},
 
 
 
 
 
 

+@article{cz15:ij,
+inhal = {no},
+domainehal = {INFO:INFO_DC, INFO:INFO_CR, INFO:INFO_MO},
+equipe = {and},
+classement = {ACLI},
+impact-factor ={0.841},
+isi-acro = {J SUPERCOMPUT},
+author = {Couturier, Rapha\"el and Ziane Khodja, Lilia},
+title = {A scalable multisplitting algorithm to solve large sparse linear systems},
+journal = {The journal of Supercomputing},
+note={{O}nline version, 10.1007/s11227-014-1367-7},
+publisher = {Springer},
+year = 2015,
+
+}
\ No newline at end of file

diff --git a/paper.tex b/paper.tex
index 83dcf1bd2c50d64bf722511daeb31547f315ddba..f141e2b66736fe8b31036260706913f72ce3d36f 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -702,7 +702,7 @@ In practice, $R$ is a dense rectangular matrix belonging in $\mathbb{R}^{n\times
   s}$,  with $s\ll  n$.   In order  to  minimize~\eqref{eq:01}, a  least-squares
 method such  as CGLS ~\cite{Hestenes52}  or LSQR~\cite{Paige82} is  used. Remark
 that  these methods  are  more appropriate  than  a single  direct  method in  a
   s}$,  with $s\ll  n$.   In order  to  minimize~\eqref{eq:01}, a  least-squares
 method such  as CGLS ~\cite{Hestenes52}  or LSQR~\cite{Paige82} is  used. Remark
 that  these methods  are  more appropriate  than  a single  direct  method in  a

-parallel context.
+parallel context. CGLS has recently been used to improve the performance of multisplitting algorithms \cite{cz15:ij}.

 
 
 
 
 
 


@@ -1055,7 +1055,7 @@ the least-squares method which corresponds to 15.
 
 \begin{figure}[htbp]
 \centering
 
 \begin{figure}[htbp]
 \centering

-  \includegraphics[width=0.45\textwidth]{nb_iter_sec_ex15_juqueen}
+  \includegraphics[width=0.5\textwidth]{nb_iter_sec_ex15_juqueen}

 \caption{Number of iterations per second with ex15 and the same parameters as in Table~\ref{tab:03} (weak scaling)}
 \label{fig:01}
 \end{figure}
 \caption{Number of iterations per second with ex15 and the same parameters as in Table~\ref{tab:03} (weak scaling)}
 \label{fig:01}
 \end{figure}


@@ -1160,7 +1160,7 @@ taken into account with TSIRM.
 
 \begin{figure}[htbp]
 \centering
 
 \begin{figure}[htbp]
 \centering

-  \includegraphics[width=0.45\textwidth]{nb_iter_sec_ex54_curie}
+  \includegraphics[width=0.5\textwidth]{nb_iter_sec_ex54_curie}

 \caption{Number of iterations per second with ex54 and the same parameters as in Table~\ref{tab:05} (strong scaling)}
 \label{fig:02}
 \end{figure}
 \caption{Number of iterations per second with ex54 and the same parameters as in Table~\ref{tab:05} (strong scaling)}
 \label{fig:02}
 \end{figure}


@@ -1228,7 +1228,7 @@ implemented in PETSc.
 %%%*********************************************************
 \section*{Acknowledgment}
 This  paper  is   partially  funded  by  the  Labex   ACTION  program  (contract
 %%%*********************************************************
 \section*{Acknowledgment}
 This  paper  is   partially  funded  by  the  Labex   ACTION  program  (contract

-ANR-11-LABX-01-01).   We acknowledge PRACE  for awarding  us access  to resources
+ANR-11-LABX-01-01).   We acknowledge the Mesocentre of Franche-Comte and PRACE  for awarding  us access  to resources

 Curie and Juqueen respectively based in France and Germany.
 
 
 Curie and Juqueen respectively based in France and Germany.