X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/ac3339a8c244d2a3f928d2c0d3539775b5a04e29..a91615879d7d661f352b74c8d4fa5c883f324acf:/hpcc.tex

diff --git a/hpcc.tex b/hpcc.tex
index d8c9a8c..529e9c1 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -692,20 +692,17 @@ elements.
 \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 allows us to 
-reach the following three objectives: 
+reach the following two 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 ensure the algorithm convergence with a reasonable time and
-iteration number ;
-\item and finally and more importantly, to find the correct combination 
-of the cluster and network specifications permitting to save time in 
-executing the algorithm in asynchronous mode.
+\item  To have  a flexible  configurable execution  platform that  allows  us to
+  simulate algorithms for  which execution of all parts of
+  the  code is  necessary. Using  simulations before  real executions  is  a nice
+  solution to detect potential scalability problems.
+
+\item To test the combination of the cluster and network specifications permitting to execute an asynchronous algorithm faster than a synchronous one.
 \end{enumerate}
-Our results have shown that in certain conditions, asynchronous mode is 
-speeder up to \np[\%]{40} comparing to the synchronous GMRES method
+Our results have shown that with two distant clusters, the asynchronous multisplitting is faster to \np[\%]{40} compared to the synchronous GMRES method
 which is not negligible for solving complex practical problems with more 
 and more increasing size.
 
@@ -715,7 +712,7 @@ demonstrated an original solution to optimize the use of a simulation
 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}