From: raphael couturier <couturie@extinction>
Date: Mon, 28 Apr 2014 14:07:37 +0000 (+0200)
Subject: suite
X-Git-Tag: hpcc2014_submission~30
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/commitdiff_plain/a91615879d7d661f352b74c8d4fa5c883f324acf?hp=-c

suite
---

a91615879d7d661f352b74c8d4fa5c883f324acf
diff --git a/hpcc.tex b/hpcc.tex
index 7d96f2b..529e9c1 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -692,22 +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 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 
-of the cluster and network specifications permitting to save time in 
-executing the algorithm in asynchronous mode.
+  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.