X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/abc7ee50fcd018c2c756f80d084b182a712b245e..ac3339a8c244d2a3f928d2c0d3539775b5a04e29:/hpcc.tex?ds=sidebyside

diff --git a/hpcc.tex b/hpcc.tex
index 622a2f0..d8c9a8c 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -82,8 +82,8 @@ what parameters  could influence or not  the behaviors of an  algorithm. In this
 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.
 
 
@@ -395,9 +395,9 @@ processor is designated (for example the processor with rank 1) and masters of
 all clusters are interconnected by a virtual unidirectional ring network (see
 Figure~\ref{fig:4.1}). During the resolution, a Boolean token circulates around
 the virtual ring from a master processor to another until the global convergence
-is achieved. So starting from the cluster with rank 1, each master processor $i$
+is achieved. So starting from the cluster with rank 1, each master processor $\ell$
 sets the token to \textit{True} if the local convergence is achieved or to
-\textit{False} otherwise, and sends it to master processor $i+1$. Finally, the
+\textit{False} otherwise, and sends it to master processor $\ell+1$. Finally, the
 global convergence is detected when the master of cluster 1 receives from the
 master of cluster $L$ a token set to \textit{True}. In this case, the master of
 cluster 1 broadcasts a stop message to masters of other clusters. In this work,
@@ -657,7 +657,7 @@ Note that the program was run with the following parameters:
 
 After analyzing the outputs, generally, for the two clusters including one hundred hosts configuration (Tables~\ref{tab.cluster.2x50}), some combinations of parameters affecting
 the results have given a relative gain more than 2.5, showing the effectiveness of the
-asynchronous multiplsitting  compared to GMRES with two distant clusters.
+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
@@ -690,10 +690,8 @@ elements.
 %\LZK{Ma question est: le bandwidth et latency sont ceux inter-clusters ou pour les deux inter et intra cluster??}
 %\CER{Définitivement, les paramètres réseaux variables ici se rapportent au réseau INTER cluster.}
 \section{Conclusion}
-The experimental results on executing a parallel iterative algorithm in 
-asynchronous mode on an environment simulating a large scale of virtual 
-computers organized with interconnected clusters have been presented. 
-Our work has demonstrated that using such a simulation tool allow us to 
+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: 
 
 \begin{enumerate}
@@ -723,7 +721,7 @@ We will also have to increase the size of the input problem which will require t
 \section*{Acknowledgment}
 
 This work is partially funded by the Labex ACTION program (contract ANR-11-LABX-01-01).
-\todo[inline]{The authors would like to thank\dots{}}
+%\todo[inline]{The authors would like to thank\dots{}}
 
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