RCE : Point decimal sur les graphiques

[rce2015.git] / paper.tex

diff --git a/paper.tex b/paper.tex
index 76a9614eea321964ca08743540ba69e26d766191..1391f0f3c275a4e255b7f2746bcf65a5fa08b703 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -588,6 +588,7 @@ efficient for distributed systems with high latency networks.
 \includegraphics[width=100mm]{cluster_x_nodes_n1_x_n2.pdf}
 \caption{Various grid configurations with networks $N1$ vs. $N2$}
 \LZK{CE, remplacer les ``,'' des décimales par un ``.''}
+\RCE{ok}
 \label{fig:02}
 \end{figure}
 
@@ -658,11 +659,12 @@ In this section,  the SimGrid simulator is  used to compare the  behavior of the
 two-stage algorithm in  asynchronous mode  with GMRES  in synchronous  mode.  Several
 benchmarks have  been performed with  various combinations of the  grid resources
 (CPU, Network, matrix size, \ldots). The test  conditions are summarized
-in  Table~\ref{tab:07}. In  order to  compare  the execution  times, this table
+in  Table~\ref{tab:02}. In  order to  compare  the execution  times, Table~\ref{tab:03}
 reports the  relative gain between both  algorithms. It is defined  by the ratio
 between  the   execution  time  of   GMRES  and   the  execution  time   of  the
 multisplitting.  
 \LZK{Quelle table repporte les gains relatifs?? Sûrement pas Table II !!}
+\RCE{Table III avec la nouvelle numerotation}
 The  ratio  is  greater  than  one  because  the  asynchronous
 multisplitting version is faster than GMRES.
 
@@ -678,7 +680,7 @@ multisplitting version is faster than GMRES.
  Residual error precision                & $10^{-5}$ to $10^{-9}$\\ \hline \\
  \end{tabular}
 \caption{Test conditions: GMRES in synchronous mode vs. Krylov two-stage in asynchronous mode}
-\label{tab:07}
+\label{tab:02}
 \end{table}
 
 
@@ -719,7 +721,7 @@ multisplitting version is faster than GMRES.
   \end{mytable}
 %\end{table}
  \caption{Relative gains of the two-stage multisplitting algorithm compared with the classical GMRES}
- \label{tab:08}
+ \label{tab:03}
 \end{table}
 
 Again,  comprehensive and  extensive tests  have been  conducted with  different
@@ -734,9 +736,8 @@ geographically distant clusters through the internet.
 
 
 \section{Conclusion}
-
 In this paper we have presented the simulation of the execution of three
-different parallel solvers on some multi-core architectures. We have show that
+different parallel solvers on some multi-core architectures. We have shown that
 the SimGrid toolkit is an interesting simulation tool that has allowed us to
 determine  which method  to choose  given a  specified multi-core  architecture.
 Moreover the simulated results are in accordance (i.e. with the same order of
@@ -758,7 +759,7 @@ converge and so to very different execution times.
 In future works, we  plan to investigate how to simulate  the behavior of really
 large scale  applications. For  example, if  we are  interested to  simulate the
 execution of the solvers of this paper with thousand or even dozens of thousands
-or core,  it is not possible  to do that with  SimGrid. In fact, this  tool will
+of cores,  it is not possible  to do that with  SimGrid. In fact, this  tool will
 make the real computation. So we plan to focus our research on that problematic.