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{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})
 \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{}}
 
   \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]}
 
 \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 
 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 
 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 
 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, 
 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,
 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.
 
 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}
   \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}
 
   \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}
   \centering
   \caption{3 clusters X 33 nodes}
   \label{tab.cluster.3x33}

+  \AG{Le fichier manque.}

   \includegraphics[width=209pt]{img2.jpg}
 \end{table}
 
   \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}
   \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}
 %  \includegraphics[width=160pt]{img3.jpg}
   \includegraphics[scale=0.5]{img3.jpg}
 \end{table}