paper, we show that it is interesting to use SimGrid to simulate the behaviors
of asynchronous iterative algorithms. For that, we compare the behaviour of a
synchronous GMRES algorithm with an asynchronous multisplitting one with
-simulations in which we choose some parameters. Both codes are real MPI
-codes. Simulations allow us to see when the multisplitting algorithm can be more
+simulations which let us easily choose some parameters. Both codes are real MPI
+codes ans simulations allow us to see when the asynchronous multisplitting algorithm can be more
efficient than the GMRES one to solve a 3D Poisson problem.
reach the following three objectives:
\begin{enumerate}
-\item To have a flexible configurable execution platform resolving the
-hard exercise to access to very limited but so solicited physical
-resources;
+\item To have a flexible configurable execution platform that allows us to
+ simulate asynchronous iterative algorithm for which execution of all parts of
+ the code is necessary. Using simulations before real execution is a nice
+ solution to detect the scalability problems.
+
\item to ensure the algorithm convergence with a reasonable time and
iteration number ;
\item and finally and more importantly, to find the correct combination
tool to run efficiently an iterative parallel algorithm in asynchronous
mode in a grid architecture.
-For our futur works, we plan to extend our experimentations to larger scale platforms by increasing the number of computing cores and the number of clusters.
+In future works, we plan to extend our experimentations to larger scale platforms by increasing the number of computing cores and the number of clusters.
We will also have to increase the size of the input problem which will require the use of a more powerful simulation platform. At last, we expect to compare our simulation results to real execution results on real architectures in order to experimentally validate our study.
\section*{Acknowledgment}
