X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/d0df474d3df1a66a6e43d1513fc3e9ed1248d2ed..0ed25093da14942800a6808b24fe51623cb882d3:/hpcc.tex

diff --git a/hpcc.tex b/hpcc.tex
index 22fa047..6e262b1 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -162,7 +162,8 @@ network  platforms  are   the  bandwidth  and  the  latency   of  inter  cluster
 network. Parameters on the cluster's architecture are the number of machines and
 the  computation power  of a  machine.  Simulations show  that the  asynchronous
 multisplitting algorithm  can solve the  3D Poisson problem  approximately twice
-faster than GMRES with two distant clusters.
+faster than GMRES with two distant clusters. In this way, we present an original solution to optimize the use of a simulation 
+tool to run efficiently an  asynchronous iterative parallel algorithm in a grid architecture
 
 
 
@@ -661,8 +662,8 @@ the results have given a relative gain more than 2.5, showing the effectiveness
 asynchronous multisplitting  compared to GMRES with two distant clusters.
 
 With these settings, Table~\ref{tab.cluster.2x50} shows
-that after setting the bandwidth of the  inter cluster network to  \np[Mbit/s]{5} and a latency in order of one hundredth of millisecond and a processor power
-of one GFlops, an efficiency of about \np[\%]{40} is
+that after setting the bandwidth of the  inter cluster network to  \np[Mbit/s]{5}, the latency to $20$ millisecond and the processor power
+to one GFlops, an efficiency of about \np[\%]{40} is
 obtained in asynchronous mode for a matrix size of $62^3$ elements. It is noticed that the result remains
 stable even we vary the residual error precision from \np{E-5} to \np{E-9}. By
 increasing the matrix size up to $100^3$ elements, it was necessary to increase the
@@ -692,7 +693,7 @@ elements.
 %\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 allows us to 
+In this work, we show that SimGrid is an efficient simulation tool that allows us to 
 reach the following two objectives: 
 
 \begin{enumerate}