Note that image files are missing.

[hpcc2014.git] / hpcc.tex

diff --git a/hpcc.tex b/hpcc.tex
index 2e791d7e35b2b126e4a090d06c28a67bd1522cd8..93972da7af155cb6ea41a05f6b138aa4c14eacfb 100644 (file)
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -8,7 +8,6 @@
 \usepackage{algpseudocode}
 %\usepackage{amsthm}
 \usepackage{graphicx}
-%\usepackage{xspace}
 \usepackage[american]{babel}
 % Extension pour les liens intra-documents (tagged PDF)
 % et l'affichage correct des URL (commande \url{http://example.com})
@@ -22,6 +21,11 @@
   \renewcommand*\npunitcommand[1]{\text{#1}}
   \npthousandthpartsep{}}
 
+\usepackage{xspace}
+\usepackage[textsize=footnotesize]{todonotes}
+\newcommand{\AG}[2][inline]{%
+  \todo[color=green!50,#1]{\sffamily\textbf{AG:} #2}\xspace}
+
 \algnewcommand\algorithmicinput{\textbf{Input:}}
 \algnewcommand\Input{\item[\algorithmicinput]}
 
@@ -71,13 +75,13 @@ iterations ($X_{n +1} = f(X_{n})$) from an initial value $X_{0}$ to find
 an approximate value $X^*$ of the solution with a very low
 residual error. Several well-known methods demonstrate the convergence 
 of these algorithms. Generally, to reduce the complexity and the 
-execution time, the problem is divided into several "pieces" that will 
+execution time, the problem is divided into several \emph{pieces} that will
 be solved in parallel on multiple processing units. The latter will 
 communicate each intermediate results before a new iteration starts 
 until the approximate solution is reached. These distributed parallel 
-computations can be performed either in "synchronous" communication mode 
+computations can be performed either in \emph{synchronous} communication mode
 where a new iteration begin only when all nodes communications are 
-completed, either "asynchronous" mode where processors can continue 
+completed, either \emph{asynchronous} mode where processors can continue
 independently without or few synchronization points. Despite the 
 effectiveness of iterative approach, a major drawback of the method is 
 the requirement of huge resources in terms of computing capacity, 
@@ -224,7 +228,7 @@ A priori, obtaining a speedup less than 1 would be difficult in a local area
 network configuration where the synchronous mode will take advantage on the rapid
 exchange of information on such high-speed links. Thus, the methodology adopted
 was to launch the application on clustered network. In this last configuration,
-degrading the inter-cluster network performance will "penalize" the synchronous
+degrading the inter-cluster network performance will \emph{penalize} the synchronous
 mode allowing to get a speedup lower than 1. This action simulates the case of
 clusters linked with long distance network like Internet.
 
@@ -270,6 +274,7 @@ 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!}
   \includegraphics[width=209pt]{img1.jpg}
 \end{table}
 
@@ -277,6 +282,7 @@ lat latency, \dots{}).
   \centering
   \caption{3 clusters X 33 nodes}
   \label{tab.cluster.3x33}
+  \AG{Le fichier manque.}
   \includegraphics[width=209pt]{img2.jpg}
 \end{table}
 
@@ -284,6 +290,7 @@ lat latency, \dots{}).
   \centering
   \caption{3 clusters X 67 nodes}
   \label{tab.cluster.3x67}
+  \AG{Le fichier manque.}
 %  \includegraphics[width=160pt]{img3.jpg}
   \includegraphics[scale=0.5]{img3.jpg}
 \end{table}