X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/blobdiff_plain/c6459f3420747227cfe477c0e22f08499ee3e4de..7c8fb94ad3ce704f81876b1dade93846a931a5a8:/paper.tex?ds=inline

diff --git a/paper.tex b/paper.tex
index 0dc584b..46ecc39 100644
--- a/paper.tex
+++ b/paper.tex
@@ -346,19 +346,18 @@ nodes/processors for each cluster).
 In addition, the following arguments are given to the programs at runtime:
 
 \begin{itemize}
-	\item maximum number of inner and outer iterations;
-	\item inner and outer precisions;
-	\item maximum number of the GMRES restarts in the Arnorldi process;
-	\item maximum number of iterations and the tolerance threshold in classical GMRES;
-	\item tolerance threshold for outer and inner-iterations;
-	\item matrix size (N$_{x}$, N$_{y}$ and N$_{z}$) respectively on $x, y, z$ axis;
-	\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 off-diagonal value;
-	\item execution mode: synchronous or asynchronous;
-	\RCE {C'est ok la liste des arguments du programme mais si Lilia ou toi pouvez preciser pour les  arguments pour CGLS ci dessous} \RC{Vu que tu n'as pas fait varier ce paramètre, on peut ne pas en parler}
-	\item Size of matrix S;
-	\item Maximum number of iterations and tolerance threshold for CGLS.
+	\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,
+	\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.
 \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.
 
@@ -716,7 +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
@@ -732,14 +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}}