From: lilia <lilia@agora>
Date: Thu, 7 May 2015 22:49:40 +0000 (+0200)
Subject: Corriger le probleme de merge
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/commitdiff_plain/49ee5215a4f7de973138cd830c4b5506e6497a34

Corriger le probleme de merge
---

diff --git a/paper.tex b/paper.tex
index cb95155..fab2e82 100644
--- a/paper.tex
+++ b/paper.tex
@@ -557,7 +557,6 @@ In what follows, we will present the test conditions, the output results and our
 \begin{center}
 \begin{tabular}{ll }
  \hline
-<<<<<<< HEAD
  Grid architecture & 2$\times$16, 4$\times$8, 4$\times$16 and 8$\times$8\\ %\hline
  Network           & N1 : $bw$=1Gbits/s, $lat$=5$\times$10$^{-5}$ \\ %\hline
  \multirow{2}{*}{Matrix size}  & N$_{x}$ $\times$ N$_{y}$ $\times$ N$_{z}$ =150 $\times$ 150 $\times$ 150\\ %\hline
@@ -565,20 +564,11 @@ In what follows, we will present the test conditions, the output results and our
  \end{tabular}
 \caption{Test conditions: various grid configurations with the matrix sizes 150$^3$ or 170$^3$}
 \LZK{Ce sont les caractéristiques du réseau intra ou inter clusters? Ce n'est pas précisé...}
-=======
- Grid Architecture & 2 $\times$ 16, 4 $\times$ 8, 4 $\times$ 16 and 8 $\times$ 8\\ %\hline
- Inter Network N2 & bw=1Gbits/s - lat=5.10$^{-5}$ \\ %\hline
- Input matrix size & N$_{x}$ $\times$ N$_{y}$ $\times$ N$_{z}$ =150 $\times$ 150 $\times$ 150\\ %\hline
- - &  N$_{x}$ $\times$ N$_{y}$ $\times$ N$_{z}$  =170 $\times$ 170 $\times$ 170    \\ \hline
- \end{tabular}
-\caption{Test conditions: various grid configurations with the input matrix size N$_{x}$=N$_{y}$=N$_{z}$=150 or 170 \RC{N2 n'est pas défini..}\RC{Nx est défini, Ny? Nz?}
-\AG{La lettre 'x' n'est pas le symbole de la multiplication. Utiliser \texttt{\textbackslash times}.  Idem dans le texte, les figures, etc.}}
->>>>>>> 2f78f080350308e2f46d8eff8d66a8e127fee583
 \label{tab:01}
 \end{center}
 \end{table}
 
-<<<<<<< HEAD
+
 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.
 %% First,  the results in  Figure~\ref{fig:01}
 %% show for all grid configurations the non-variation of the number of iterations of
@@ -586,20 +576,6 @@ In this section, we analyze the simulations conducted on various grid configurat
 %% multisplitting method.
 \RC{CE attention tu n'as pas mis de label dans tes figures, donc c'est le bordel, j'en mets mais vérifie...}
 \RC{Les légendes ne sont pas explicites...}
-=======
-
-
-
-
-In this  section, we analyze the  performance of algorithms running  on various
-grid configurations  (2 $\times$ 16, 4 $\times$ 8, 4 $\times$ 16  and 8 $\times$ 8) and using an inter-network N2 defined in the test conditions in Table~\ref{tab:01}. 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 vérifie...}
-%\RC{Les légendes ne sont pas explicites...}
->>>>>>> 2f78f080350308e2f46d8eff8d66a8e127fee583
 
 \begin{figure} [ht!]
   \begin{center}
@@ -611,7 +587,6 @@ multisplitting method.
   \label{fig:01}
 \end{figure}
 
-<<<<<<< HEAD
 The execution  times between  the two algorithms  is significant  with different
 grid architectures, even  with the same number of processors  (for example, 2x16
 and  4x8). We  can  observe  the low  sensitivity  of  the Krylov multisplitting  method
@@ -620,14 +595,6 @@ in the  grid: in  average, the GMRES  (resp. Multisplitting)  algorithm performs
 $40\%$ better (resp. $48\%$) when running from 2x16=32 to 8x8=64 processors. 
 \RC{pas très clair, c'est pas précis de dire qu'un algo perform mieux qu'un autre, selon quel critère?}
 \LZK{A revoir toute cette analyse... Le multi est plus performant que GMRES. Les temps d'exécution de multi sont sensibles au nombre de CLUSTERS. Il est moins performant pour un nombre grand de cluster. Avez vous d'autres remarques?}
-=======
-
-Secondly, 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  observ  the sensitivity  of  the Krylov multisplitting  method
-(compared with the classical GMRES) when scaling up the number of the processors
-in the  grid: in  average, the reduction of the execution time for GMRES  (resp. Multisplitting)  algorithm is around $40\%$ (resp. around $48\%$) when running from 32 (grid 2 $\times$ 16) to 64 processors (grid 8 $\times$ 8) processors. \RC{pas très clair, c'est pas précis de dire qu'un algo perform mieux qu'un autre, selon quel critère?}
->>>>>>> 2f78f080350308e2f46d8eff8d66a8e127fee583
 
 \subsubsection{Simulations for two different inter-clusters network speeds \\}
 
@@ -635,32 +602,18 @@ in the  grid: in  average, the reduction of the execution time for GMRES  (resp.
 \begin{center}
 \begin{tabular}{ll}
  \hline
-<<<<<<< HEAD
  Grid architecture        & 2$\times$16, 4$\times$8\\ %\hline
  \multirow{2}{*}{Network} & N1: $bw$=1Gbs, $lat$=5$\times$10$^{-5}$ \\ %\hline
                           & N2: $bw$=10Gbs, $lat$=8$\times$10$^{-6}$ \\
  Matrix size              & $N_{x} \times N_{y} \times N_{z} =150 \times 150 \times 150$\\ \hline
  \end{tabular}
 \caption{Test conditions: grid configurations 2$\times$16 and 4$\times$8 with networks N1 vs. N2}
-=======
- Grid Architecture & 2 $\times$ 16, 4 $\times$ 8\\ %\hline
- Inter Networks & N1 : bw=10Gbs-lat=8.10$^{-6}$ \\ %\hline
- - & N2 : bw=1Gbs-lat=5.10$^{-5}$ \\
- Input matrix size & $N_{x} \times N_{y} \times N_{z} =150 \times 150 \times 150$\\ \hline
- \end{tabular}
-\caption{Test conditions: grid 2 $\times$ 16 and 4 $\times$ 8 with  networks N1 vs N2}
->>>>>>> 2f78f080350308e2f46d8eff8d66a8e127fee583
 \label{tab:02}
 \end{center}
 \end{table}
 
-<<<<<<< HEAD
-These experiments  compare the  behavior of  the algorithms  running first  on a
-slow inter-cluster  network (N1) and  also on  a more performant  network (N2). \RC{Il faut définir cela avant...}
-=======
 In this section, the experiments  compare the  behavior of  the algorithms  running on a
-speeder inter-cluster  network (N1) and  also on  a less performant  network (N2) respectively defined in the test conditions Table~\ref{tab:02}. \RC{Il faut définir cela avant...}
->>>>>>> 2f78f080350308e2f46d8eff8d66a8e127fee583
+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 is about $2$. 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\%.