X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/70f82cf5e87fbbebce020a9163579a602385a7ff..e421bb1806cde3dfe6a238e56119fbae3025fe9d:/hpcc.tex?ds=sidebyside

diff --git a/hpcc.tex b/hpcc.tex
index a5f2768..94e9ee7 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -25,10 +25,12 @@
 \usepackage[textsize=footnotesize]{todonotes}
 \newcommand{\AG}[2][inline]{%
   \todo[color=green!50,#1]{\sffamily\textbf{AG:} #2}\xspace}
-\newcommand{\RC}[2][inline]{%
-  \todo[color=red!10,#1]{\sffamily\textbf{RC:} #2}\xspace}
+\newcommand{\DL}[2][inline]{%
+  \todo[color=yellow!50,#1]{\sffamily\textbf{DL:} #2}\xspace}
 \newcommand{\LZK}[2][inline]{%
   \todo[color=blue!10,#1]{\sffamily\textbf{LZK:} #2}\xspace}
+\newcommand{\RC}[2][inline]{%
+  \todo[color=red!10,#1]{\sffamily\textbf{RC:} #2}\xspace}
 
 \algnewcommand\algorithmicinput{\textbf{Input:}}
 \algnewcommand\Input{\item[\algorithmicinput]}
@@ -89,15 +91,14 @@ from the current work, a simulated environment like Simgrid provides
 accurate results which are difficult or even impossible to obtain in a 
 physical platform by exploiting the flexibility of the simulator on the 
 computing units clusters and the network structure design. Our 
-experimental outputs showed a saving of up to 40 \% for the algorithm 
+experimental outputs showed a saving of up to \np[\%]{40} for the algorithm
 execution time in asynchronous mode compared to the synchronous one with 
-a residual precision up to E-11. Such successful results open 
+a residual precision up to \np{E-11}. Such successful results open
 perspectives on experimentations for running the algorithm on a 
 simulated large scale growing environment and with larger problem size. 
 
-Keywords : Algorithm distributed iterative asynchronous simulation 
-simgrid
-
+% no keywords for IEEE conferences
+% Keywords: Algorithm distributed iterative asynchronous simulation simgrid
 \end{abstract}
 
 \section{Introduction}
@@ -170,16 +171,11 @@ our future work after the results.
  
 \section{The asynchronous iteration model}
 
-Décrire le modèle asynchrone. Je m'en charge (DL)
+\DL{Décrire le modèle asynchrone. Je m'en charge}
 
 \section{SimGrid}
 
-Décrire SimGrid~\cite{casanova+legrand+quinson.2008.simgrid} (Arnaud)
-
-
-
-
-
+\AG{Décrire SimGrid~\cite{casanova+legrand+quinson.2008.simgrid} (Arnaud)}
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -332,7 +328,10 @@ lat latency, \dots{}).
   \centering
   \caption{2 clusters X 50 nodes}
   \label{tab.cluster.2x50}
-  \AG{Les images manquent dans le dépôt Git. Si ce sont vraiment des tableaux, utiliser un format vectoriel (eps ou pdf), et surtout pas de jpeg!}
+  \AG{Ces tableaux (\ref{tab.cluster.2x50}, \ref{tab.cluster.3x33} et
+    \ref{tab.cluster.3x67}) sont affreux. Utiliser un format vectoriel (eps ou
+    pdf) ou, mieux, les réécrire en \LaTeX{}. Réécrire les légendes proprement
+    également (\texttt{\textbackslash{}times} au lieu de \texttt{X} par ex.)}
   \includegraphics[width=209pt]{img1.jpg}
 \end{table}
 
@@ -340,7 +339,7 @@ lat latency, \dots{}).
   \centering
   \caption{3 clusters X 33 nodes}
   \label{tab.cluster.3x33}
-  \AG{Le fichier manque.}
+  \AG{Refaire le tableau.}
   \includegraphics[width=209pt]{img2.jpg}
 \end{table}
 
@@ -348,7 +347,7 @@ lat latency, \dots{}).
   \centering
   \caption{3 clusters X 67 nodes}
   \label{tab.cluster.3x67}
-  \AG{Le fichier manque.}
+  \AG{Refaire le tableau.}
 %  \includegraphics[width=160pt]{img3.jpg}
   \includegraphics[scale=0.5]{img3.jpg}
 \end{table}
@@ -378,7 +377,7 @@ For the 3 clusters architecture including a total of 100 hosts, Table~\ref{tab.c
 that it was difficult to have a combination which gives an efficiency of
 asynchronous below \np[\%]{80}. Indeed, for a matrix size of 62 elements, equality
 between the performance of the two modes (synchronous and asynchronous) is
-achieved with an inter cluster of \np[Mbits/s]{10} and a latency of \np{E-1} ms. To
+achieved with an inter cluster of \np[Mbits/s]{10} and a latency of \np[ms]{E-1}. To
 challenge an efficiency by \np[\%]{78} with a matrix size of 100 points, it was
 necessary to degrade the inter cluster network bandwidth from 5 to 2 Mbit/s.
 
@@ -408,7 +407,7 @@ executing the algorithm in asynchronous mode.
 \setcounter{numberedCntD}{\theenumi}
 \end{enumerate}
 Our results have shown that in certain conditions, asynchronous mode is 
-speeder up to 40 \% than executing the algorithm in synchronous mode 
+speeder up to \np[\%]{40} than executing the algorithm in synchronous mode
 which is not negligible for solving complex practical problems with more 
 and more increasing size.