X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/blobdiff_plain/18a590b4593843d38f5012c20a06f000388301cf..7c8fb94ad3ce704f81876b1dade93846a931a5a8:/paper.tex

diff --git a/paper.tex b/paper.tex
index b9d11d4..46ecc39 100644
--- a/paper.tex
+++ b/paper.tex
@@ -349,14 +349,15 @@ In addition, the following arguments are given to the programs at runtime:
 	\item maximum number of inner iterations $\MIG$ and outer iterations $\MIM$,
 	\item inner precision $\TOLG$ and outer precision $\TOLM$,
 	\item matrix sizes of the 3D Poisson problem: N$_{x}$, N$_{y}$ and N$_{z}$ on axis $x$, $y$ and $z$ respectively,
-	\item matrix diagonal value is fixed to $6.0$ for synchronous Krylov multisplitting experiments and $6.2$ for asynchronous block Jacobi experiments, \RC{CE tu vérifies, je dis ca de tête}
+	\item matrix diagonal value is fixed to $6.0$ for synchronous Krylov multisplitting experiments and $6.2$ for asynchronous block Jacobi experiments,
 	\item matrix off-diagonal value is fixed to $-1.0$,
 	\item number of vectors in matrix $S$ (i.e. value of $s$),
 	\item maximum number of iterations $\MIC$ and precision $\TOLC$ for CGLS method,
         \item maximum number of iterations and precision for the classical GMRES method,
         \item maximum number of restarts for the Arnorldi process in GMRES method,
-      	\item execution mode: synchronous or asynchronous,
+      	\item execution mode: synchronous or asynchronous.
 \end{itemize}
+\LZK{CE pourrais tu vérifier et confirmer les valeurs des éléments diag et off-diag de la matrice?}
 
 It should also be noticed that both solvers have been executed with the Simgrid selector \texttt{-cfg=smpi/running\_power} which determines the computational power (here 19GFlops) of the simulator host machine.
 
@@ -714,7 +715,7 @@ get    the   highest    \textit{"relative    gain"}   (exec\_time$_{GMRES}$    /
 exec\_time$_{multisplitting}$) in comparison with the classical GMRES time.
 
 
-The test conditions are summarized in the table below : \\
+The test conditions are summarized in the table below: \\
 
 \begin{figure} [ht!]
 \centering
@@ -730,14 +731,14 @@ The test conditions are summarized in the table below : \\
 \end{figure}
 
 Again,  comprehensive and  extensive tests  have been  conducted with  different
-parametes as  the CPU power, the  network parameters (bandwidth and  latency) in
-the simulator tool  and with different problem size. The  relative gains greater
-than 1  between the  two algorithms have  been captured after  each step  of the
-test.   In  Figure~\ref{table:01}  are  reported the  best  grid  configurations
-allowing the  multisplitting method to  be more than  2.5 times faster  than the
+parameters as  the CPU power, the  network parameters (bandwidth and  latency)
+and with different problem size. The  relative gains greater than $1$  between the
+two algorithms have  been captured after  each step  of the test.   In
+Figure~\ref{table:01}  are  reported the  best  grid  configurations allowing
+the  multisplitting method to  be more than  $2.5$ times faster  than the
 classical  GMRES.  These  experiments also  show the  relative tolerance  of the
 multisplitting algorithm when using a low speed network as usually observed with
-geographically distant clusters throuth the internet.
+geographically distant clusters through the internet.
 
 % use the same column width for the following three tables
 \newlength{\mytablew}\settowidth{\mytablew}{\footnotesize\np{E-11}}