X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/blobdiff_plain/0ff5badea3e5156e9795cf5724f3dffed49ca7b5..2110422a08b1d1879e5dd4435e37b6f372327aa1:/paper.tex

diff --git a/paper.tex b/paper.tex
index 523716f..b9187dd 100644
--- a/paper.tex
+++ b/paper.tex
@@ -495,6 +495,7 @@ latency of 8.10$^{-6}$ seconds (resp.  5.10$^{-5}$) for the intra-clusters links
 (resp.  inter-clusters backbone links).  \\
 
 \LZK{Il me semble que le bw et lat des deux rÃ©seaux varient dans les expÃ©s d'une simu Ã  l'autre. On vire la derniÃ¨re phrase?}
+\RC{il me semble qu'on peut laisser ca}
 
 \textbf{Step 5}: Conduct an extensive and comprehensive testings
 within these configurations by varying the key parameters, especially
@@ -540,12 +541,15 @@ and  between distant  clusters.  This parameter is application dependent.
 In the scope  of this paper, our  first objective is to analyze  when the Krylov
 two-stage method has  better  performance  than   the  classical  GMRES method. With a synchronous  iterative method, better performance means a
 smaller number of iterations and execution time before reaching the convergence.
-For a systematic study,  the experiments  should figure  out  that, for  various
-grid  parameters values, the simulator will confirm Multisplitting method  better performance compared to classical GMRES, particularly on poor and slow networks.
-\LZK{Pas du tout claire la derniÃ¨re phrase (For a systematic...)!!}
-\RCE { Reformule autrement}
+In what follows, we will present the test conditions, the output results and our comments.
+
+%%RAPH : on vire ca, c'est pas clair et pas important
+%For a systematic study,  the experiments  should figure  out  that, for  various
+%grid  parameters values, the simulator will confirm Multisplitting method  better performance compared to classical GMRES, particularly on poor and slow networks.
+%\LZK{Pas du tout claire la derniÃ¨re phrase (For a systematic...)!!}
+%\RCE { Reformule autrement}
+
 
-In what follows, we will present the test conditions, the output results and our comments.\\
 
 %\subsubsection{Execution of the algorithms on various computational grid architectures and scaling up the input matrix size}
 \subsubsection{Simulations for various grid architectures and scaling-up matrix sizes}
@@ -563,33 +567,42 @@ In what follows, we will present the test conditions, the output results and our
   &  N$_{x}$ $\times$ N$_{y}$ $\times$ N$_{z}$  =170 $\times$ 170 $\times$ 170    \\ \hline
  \end{tabular}
 \caption{Test conditions: various grid configurations with the matrix sizes 150$^3$ or 170$^3$}
-\LZK{Ce sont les caractÃ©ristiques du rÃ©seau intra ou inter clusters? Ce n'est pas prÃ©cisÃ©...}
-\RCE{oui c est precise}
+%\LZK{Ce sont les caractÃ©ristiques du rÃ©seau intra ou inter clusters? Ce n'est pas prÃ©cisÃ©...}
+%\RCE{oui c est precise}
 \label{tab:01}
 \end{center}
 \end{table}
 
 
-In this section, we analyze the simulations conducted on various grid configurations presented in Table~\ref{tab:01}. Figure~\ref{fig:01} shows, for all grid configurations and a given matrix size, a non-variation in the number of iterations for the classical GMRES algorithm, which is not the case of the Krylov two-stage algorithm.
+In  this  section,  we  analyze   the  simulations  conducted  on  various  grid
+configurations presented  in Table~\ref{tab:01}. It  should be noticed  that two
+networks are considered: N1 is  the network between clusters (inter-cluster) and
+N2 is the network inside  a cluster (intra-cluster).  Figure~\ref{fig:01} shows,
+for all  grid configurations  and a  given matrix size,  a non-variation  in the
+number of iterations for the classical GMRES algorithm, which is not the case of
+the Krylov two-stage algorithm.
 %% First,  the results in  Figure~\ref{fig:01}
 %% show for all grid configurations the non-variation of the number of iterations of
 %% classical  GMRES for  a given  input matrix  size; it is not  the case  for the
 %% multisplitting method.
-\RC{CE attention tu n'as pas mis de label dans tes figures, donc c'est le bordel, j'en mets mais vÃ©rifie...}
-\RC{Les lÃ©gendes ne sont pas explicites...}
-\RCE{Corrige}
+%\RC{CE attention tu n'as pas mis de label dans tes figures, donc c'est le bordel, j'en mets mais vÃ©rifie...}
+%\RC{Les lÃ©gendes ne sont pas explicites...}
+%\RCE{Corrige}
 
 \begin{figure} [ht!]
   \begin{center}
     \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$^3$
-\AG{Utiliser le point comme sÃ©parateur dÃ©cimal et non la virgule.  Idem dans les autres figures.}}
-\LZK{Pour quelle taille du problÃ¨me sont calculÃ©s les nombres d'itÃ©rations? Que reprÃ©sente le 2 Clusters x 16 Nodes with Nx=150 and Nx=170 en haut de la figure?}
-\RCE {Corrige}
+  \caption{Various grid configurations with the matrix sizes 150$^3$ and 170$^3$}
+%\AG{Utiliser le point comme sÃ©parateur dÃ©cimal et non la virgule.  Idem dans les autres figures.}
+%\LZK{Pour quelle taille du problÃ¨me sont calculÃ©s les nombres d'itÃ©rations? Que reprÃ©sente le 2 Clusters x 16 Nodes with Nx=150 and Nx=170 en haut de la figure?}
+  %\RCE {Corrige}
+    \RC{IdÃ©alement dans la lÃ©gende il faudrait insiquer Pb size=$150^3$ ou $170^3$  car pour l'instant Nx=150 ca n'indique rien concernant Ny et Nz}
   \label{fig:01}
 \end{figure}
 
+
+
 The execution  times between  the two algorithms  is significant  with different
 grid architectures, even  with the same number of processors  (for example, 2 $\times$ 16
 and  4 $\times  8$). We  can  observe  a better  sensitivity  of  the Krylov multisplitting  method
@@ -617,7 +630,8 @@ $40\%$ better (resp. $48\%$) when running from 32 (grid 2 $\times$ 16) to 64 pro
 \end{table}
 
 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 dÃ©finir cela avant...}
+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 dÃ©finir 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\%.
