Modifs section 5.4.3

diff --git a/paper.tex b/paper.tex
index da22c509a2fb6b197b95b5edb0d778f6e59ab413..f0602ca7f5a9902c0a9e8fc301a7a7f551f8eb81 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -569,7 +569,6 @@ The execution times between both algorithms is significant with different grid a
 \includegraphics[width=100mm]{cluster_x_nodes_nx_150_and_nx_170.pdf}
 \end{center}
 \caption{Various grid configurations with the matrix sizes 150$^3$ and 170$^3$}
 \includegraphics[width=100mm]{cluster_x_nodes_nx_150_and_nx_170.pdf}
 \end{center}
 \caption{Various grid configurations with the matrix sizes 150$^3$ and 170$^3$}

-\LZK{CE, la légende de la Figure 3 est trop large. Remplacer les N$_x\times$N$_y\times$N$_z$ par $Mat1$=150$^3$ et $Mat2$=170$^3$ comme dans la Table 1}

 \label{fig:01}
 \end{figure}
 
 \label{fig:01}
 \end{figure}
 


@@ -584,13 +583,6 @@ sensitive to bad network bandwidth and latency for the inter-clusters links than
 the  GMRES algorithms.  This  means  that the  multisplitting  methods are  more
 efficient for distributed systems with high latency networks.
 
 the  GMRES algorithms.  This  means  that the  multisplitting  methods are  more
 efficient for distributed systems with high latency networks.
 

-%% 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}.
-%% %\RC{Il faut définir cela avant...}
-%% Figure~\ref{fig:02} shows that end users will reduce the execution time
-%% for  both  algorithms when using  a  grid  architecture  like  4 $\times$ 16 or  8 $\times$ 8: the reduction factor is around $2$. The results depict  also that when
-%% the  network speed  drops down (variation of 12.5\%), the  difference between  the two Multisplitting algorithms execution times can reach more than 25\%.
-

 \begin{figure}[t]
 \centering
 \includegraphics[width=100mm]{cluster_x_nodes_n1_x_n2.pdf}
 \begin{figure}[t]
 \centering
 \includegraphics[width=100mm]{cluster_x_nodes_n1_x_n2.pdf}


@@ -599,7 +591,15 @@ efficient for distributed systems with high latency networks.
 \label{fig:02}
 \end{figure}
 
 \label{fig:02}
 \end{figure}
 

+\subsubsection{Network latency impacts on performance\\}
+Figure~\ref{fig:03} shows the impact of the network latency on the performances of both algorithms. The simulation is conducted on a computational grid of 2 clusters of 16 processors each (i.e. configuration 2$\times$16) interconnected by a network of bandwidth $bw$=1Gbs to solve a 3D Poison problem of size $150^3$. According to the results, a degradation of the network latency from $8\times 10^{-6}$ to $6\times 10^{-5}$ implies an absolute execution time increase for both algorithms, but not with the same rate of degradation. The GMRES algorithm is more sensitive to the latency degradation than the Krylov two-stage algorithm. 

 
 

+\begin{figure}[t]
+\centering
+\includegraphics[width=100mm]{network_latency_impact_on_execution_time.pdf}
+\caption{Network latency impacts on execution times}
+\label{fig:03}
+\end{figure}

 
 
 
 
 
 


@@ -633,36 +633,8 @@ efficient for distributed systems with high latency networks.
 
 
 
 
 
 

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

 
 

-\begin{table} [ht!]
-\centering
-\begin{tabular}{r c }
- \hline
- Grid Architecture & 2 $\times$ 16\\ %\hline
- \multirow{2}{*}{Inter Network N1} & $bw$=1Gbs, \\ %\hline
-                          & $lat$= From 8$\times$10$^{-6}$ to  $6.10^{-5}$ second \\
- Input matrix size & $N_{x} \times N_{y} \times N_{z} = 150 \times 150 \times 150$\\ \hline
- \end{tabular}
-\caption{Test conditions: network latency impacts}
-\label{tab:03}
-\end{table}
-
-\begin{figure} [htbp]
-\centering
-\includegraphics[width=100mm]{network_latency_impact_on_execution_time.pdf}
-\caption{Network latency impacts on execution time}
-%\AG{\np{E-6}}}
-\label{fig:03}
-\end{figure}

 
 

-In Table~\ref{tab:03}, parameters  for the influence of the  network latency are
-reported.  According to the results of Figure~\ref{fig:03}, a degradation of the
-network  latency  from  $8.10^{-6}$  to $6.10^{-5}$  implies  an  absolute  time
-increase of more than $75\%$ (resp.   $82\%$) of the execution for the classical
-GMRES  (resp.   Krylov  multisplitting)  algorithm. The  execution  time  factor
-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.

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