depending on how iterations and communications are managed (for more details
readers can refer to~\cite{bcvc06:ij}). In the synchronous iterations model,
data are exchanged at the end of each iteration. All the processors must begin
-the same iteration at the same time and important idle times on processors are
+the same iteration at the same time and important and useless idle times used for synchronization on processors are
generated. It is possible to use asynchronous communications, in this case, the
model can be compared to the previous one except that data required on another
processor are sent asynchronously i.e. without stopping current computations.
This technique allows communications to be partially overlapped by computations
-but unfortunately, the overlapping is only partial and important idle times
-remain. It is clear that, in a grid computing context, where the number of
+but unfortunately, the overlapping is only partial and useless idle times used for synchronization remain.
+It is clear that, in a grid computing context, where the number of
computational nodes is large, heterogeneous and widely distributed, the idle
times generated by synchronizations are very penalizing. One way to overcome
this problem is to use the asynchronous iterations model. Here, local
languages. SMPI is the interface that has been used for the work described in
this paper. The SMPI interface implements about \np[\%]{80} of the MPI 2.0
standard~\cite{bedaride+degomme+genaud+al.2013.toward}, and supports
-applications written in C or Fortran, with little or no modifications.
+applications written in C or Fortran, with little or no modifications (cf Section IV - paragraph B).
Within SimGrid, the execution of a distributed application is simulated by a
single process. The application code is really executed, but some operations,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-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. For the synchronous GMRES method, the execution of the program raised no particular issue but in the asynchronous multisplitting method, the review of the sequence of \texttt{MPI\_Isend, MPI\_Irecv} and \texttt{MPI\_Waitall} instructions
+We did not encounter major blocking problems when adapting the multisplitting algorithm previously described to a simulation environment like SimGrid. Only, some code
+debugging has been required. 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. For the synchronous GMRES method, the execution of the program raised no particular issue but in the asynchronous multisplitting method, the review of the sequence of \texttt{MPI\_Isend, MPI\_Irecv} and \texttt{MPI\_Waitall} instructions
and with the addition of the primitive \texttt{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.}
%\CER{Définitivement, les paramètres réseaux variables ici se rapportent au réseau INTER cluster.}
\section{Conclusion}
The simulation of the execution of parallel asynchronous iterative algorithms on large scale clusters has been presented.
-In this work, we show that SimGrid is an efficient simulation tool that has enabled us to
+In this work, we show that SimGrid is one of efficient simulation tool that has enabled us to
reach the following two objectives:
\begin{enumerate}
