-We did not encounter major blocking problems when adapting the multisplitting
-algorithm previously described to a simulation environment like SimGrid unless
-some code debugging. Indeed, apart from the review of the program sequence for
-asynchronous exchanges between the six neighbors of each point in a submatrix
-within a cluster or between clusters, the algorithm was executed successfully
-with SMPI and provided identical outputs as those obtained with direct execution
-under MPI. In synchronous mode, the execution of the program raised no
-particular issue but in asynchronous mode, the review of the sequence of
-MPI\_Isend, MPI\_Irecv and MPI\_Waitall instructions and with the addition of
-the primitive MPI\_Test was needed to avoid a memory fault due to an infinite
-loop resulting from the non-convergence of the algorithm. Note here that the use
-of SMPI functions optimizer for memory footprint and CPU usage is not
-recommended knowing that one wants to get real results by simulation. As
-mentioned, upon this adaptation, the algorithm is executed as in the real life
-in the simulated environment after the following minor changes. First, all
-declared global variables have been moved to local variables for each
-subroutine. In fact, global variables generate side effects arising from the
-concurrent access of shared memory used by threads simulating each computing
-units in the SimGrid architecture. Second, the alignment of certain types of
-variables such as ``long int'' had also to be reviewed. Finally, some
-compilation errors on MPI\_Waitall and MPI\_Finalize primitives have been fixed
-with the latest version of SimGrid. In total, the initial MPI program running
-on the simulation environment SMPI gave after a very simple adaptation the same
-results as those obtained in a real environment. We have tested in synchronous
-mode with a simulated platform starting from a modest 2 or 3 clusters grid to a
-larger configuration like simulating Grid5000 with more than 1500 hosts with
-5000 cores~\cite{bolze2006grid}. Once the code debugging and adaptation were
-complete, the next section shows our methodology and experimental results.
-
-
-\section{Experimental results}
-
-When the \emph{real} application runs in the simulation environment and produces the expected results, varying the input
+We did not encounter major blocking problems when adapting the multisplitting algorithm previously described to a simulation environment like SimGrid unless some code
+debugging. Indeed, apart from the review of the program sequence for asynchronous exchanges between processors within a cluster or between clusters, the algorithm was executed successfully with SMPI and provided identical outputs as those obtained with direct execution under MPI. In synchronous
+mode, the execution of the program raised no particular issue but in asynchronous mode, the review of the sequence of MPI\_Isend, MPI\_Irecv and MPI\_Waitall instructions
+and with the addition of the primitive MPI\_Test was needed to avoid a memory fault due to an infinite loop resulting from the non-convergence of the algorithm.
+\CER{On voulait en fait montrer la simplicité de l'adaptation de l'algo a SimGrid. Les problèmes rencontrés décrits dans ce paragraphe concerne surtout le mode async}\LZK{OK. J'aurais préféré avoir un peu plus de détails sur l'adaptation de la version async}
+\CER{Le problème majeur sur l'adaptation MPI vers SMPI pour la partie asynchrone de l'algorithme a été le plantage en SMPI de Waitall après un Isend et Irecv. J'avais proposé un workaround en utilisant un MPI\_wait séparé pour chaque échange a la place d'un waitall unique pour TOUTES les échanges, une instruction qui semble bien fonctionner en MPI. Ce workaround aussi fonctionne bien. Mais après, tu as modifié le programme avec l'ajout d'un MPI\_Test, au niveau de la routine de détection de la convergence et du coup, l'échange global avec waitall a aussi fonctionné.}
+Note here that the use of SMPI functions optimizer for memory footprint and CPU usage is not recommended knowing that one wants to get real results by simulation.
+As mentioned, upon this adaptation, the algorithm is executed as in the real life in the simulated environment after the following minor changes. First, all declared
+global variables have been moved to local variables for each subroutine. In fact, global variables generate side effects arising from the concurrent access of
+shared memory used by threads simulating each computing unit in the SimGrid architecture. Second, the alignment of certain types of variables such as ``long int'' had
+also to be reviewed.
+\AG{À propos de ces problèmes d'alignement, en dire plus si ça a un intérêt, ou l'enlever.}
+\CER{Ce problème fait partie des modifications que j'ai dû faire dans l'adaptation du programme MPI vers SMPI. IL découle de la différence de la taille des mots en mémoire : en 32 bits, pour les variables declarees en long int, on garde dans les instructions de sortie (printf, sprintf, ...) le format \%lu sinon en 64 bits, on le substitue par \%llu.}
+ Finally, some compilation errors on MPI\_Waitall and MPI\_Finalize primitives have been fixed with the latest version of SimGrid.
+In total, the initial MPI program running on the simulation environment SMPI gave after a very simple adaptation the same results as those obtained in a real
+environment. We have successfully executed the code in synchronous mode using parallel GMRES algorithm compared with our multisplitting algorithm in asynchronous mode after few modifications.
+
+
+
+\section{Simulation results}
+
+When the \textit{real} application runs in the simulation environment and produces the expected results, varying the input
