retour en arrière

[rce2015.git] / paper.tex

diff --git a/paper.tex b/paper.tex
index 8bdc8f3cf5d3ee8e1bc9c31b86042ac7d4fa72a8..ab8f9abfcbef3367f53947788140445861fcb16a 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -549,9 +549,8 @@ Grid architecture                       & 2$\times$16, 4$\times$8, 4$\times$16 a
 \end{center}
 \end{table}
 
 \end{center}
 \end{table}
 

-\subsubsection{Simulations for various grid architectures and scaling-up matrix sizes}
-\  \\
-% environment
+\subsubsection{Simulations for various grid architectures and scaling-up matrix sizes\\}
+

 In  this  section,  we  analyze   the  simulations  conducted  on  various  grid
 configurations and for different sizes of the 3D Poisson problem. The parameters
 of    the    network    between    clusters    is    fixed    to    $N2$    (see
 In  this  section,  we  analyze   the  simulations  conducted  on  various  grid
 configurations and for different sizes of the 3D Poisson problem. The parameters
 of    the    network    between    clusters    is    fixed    to    $N2$    (see


@@ -573,7 +572,7 @@ The execution times between both algorithms is significant with different grid a
 \label{fig:01}
 \end{figure}
 
 \label{fig:01}
 \end{figure}
 

-\subsubsection{Simulations for two different inter-clusters network speeds \\}
+\subsubsection{Simulations for two different inter-clusters network speeds\\}

 
 In this section, the experiments  compare the  behavior of  the algorithms  running on a
 speeder inter-cluster  network (N2) and  also on  a less performant  network (N1) respectively defined in the test conditions Table~\ref{tab:02}.
 
 In this section, the experiments  compare the  behavior of  the algorithms  running on a
 speeder inter-cluster  network (N2) and  also on  a less performant  network (N1) respectively defined in the test conditions Table~\ref{tab:02}.


@@ -610,8 +609,8 @@ the  network speed  drops down (variation of 12.5\%), the  difference between  t
 
 
 
 
 
 

-\subsubsection{Network latency impacts on performance}
-\ \\
+\subsubsection{Network latency impacts on performance\\}
+

 \begin{table} [ht!]
 \centering
 \begin{tabular}{r c }
 \begin{table} [ht!]
 \centering
 \begin{tabular}{r c }


@@ -642,8 +641,8 @@ between the two algorithms  varies from 2.2 to 1.5 times  with a network latency
 decreasing from $8.10^{-6}$ to $6.10^{-5}$ second.
 
 
 decreasing from $8.10^{-6}$ to $6.10^{-5}$ second.
 
 

-\subsubsection{Network bandwidth impacts on performance}
-\ \\
+\subsubsection{Network bandwidth impacts on performance\\}
+

 \begin{table} [ht!]
 \centering
 \begin{tabular}{r c }
 \begin{table} [ht!]
 \centering
 \begin{tabular}{r c }


@@ -675,8 +674,8 @@ Figure~\ref{fig:04}). However,  in this  case, the Krylov  multisplitting method
 presents a better  performance in the considered bandwidth interval  with a gain
 of $40\%$ which is only around $24\%$ for the classical GMRES.
 
 presents a better  performance in the considered bandwidth interval  with a gain
 of $40\%$ which is only around $24\%$ for the classical GMRES.
 

-\subsubsection{Input matrix size impacts on performance}
-\ \\
+\subsubsection{Input matrix size impacts on performance\\}
+

 \begin{table} [ht!]
 \centering
 \begin{tabular}{r c }
 \begin{table} [ht!]
 \centering
 \begin{tabular}{r c }