From b9b0377c79d67208781b749176f5b98db7248db7 Mon Sep 17 00:00:00 2001 From: couturie Date: Thu, 7 May 2015 17:36:55 +0200 Subject: [PATCH] correction figure => table --- paper.tex | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/paper.tex b/paper.tex index 886390b..ac5bfc6 100644 --- a/paper.tex +++ b/paper.tex @@ -826,7 +826,7 @@ Again, comprehensive and extensive tests have been conducted with different parameters as the CPU power, the network parameters (bandwidth and latency) and with different problem size. The relative gains greater than $1$ between the two algorithms have been captured after each step of the test. In -Figure~\ref{fig:07} are reported the best grid configurations allowing +Table~\ref{tab:08} are reported the best grid configurations allowing the multisplitting method to be more than $2.5$ times faster than the classical GMRES. These experiments also show the relative tolerance of the multisplitting algorithm when using a low speed network as usually observed with @@ -841,7 +841,7 @@ geographically distant clusters through the internet. \end{tabular}} -\begin{figure}[!t] +\begin{table}[!t] \centering %\begin{table} % \caption{Relative gain of the multisplitting algorithm compared with the classical GMRES} @@ -868,10 +868,9 @@ geographically distant clusters through the internet. \hline \end{mytable} %\end{table} - \caption{Relative gain of the multisplitting algorithm compared with the classical GMRES -\AG{C'est un tableau, pas une figure}} - \label{fig:07} -\end{figure} + \caption{Relative gain of the multisplitting algorithm compared with the classical GMRES} + \label{tab:08} +\end{table} \section{Conclusion} -- 2.39.5