X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/blobdiff_plain/6cf9ae48517bcca32ee10fc0e2140e3df0386bd7..1a0318a4e9b5af6c26d37412f90d56932f69286d:/paper.tex?ds=sidebyside

diff --git a/paper.tex b/paper.tex
index 6ac52c3..d65672a 100644
--- a/paper.tex
+++ b/paper.tex
@@ -246,7 +246,8 @@ by simulation are in accordance with reality i.e. of the same order of
 magnitude. To our knowledge, there is no study on this problematic.
 
 \section{SimGrid}
- \label{sec:simgrid}
+\label{sec:simgrid}
+SimGrid~\cite{SimGrid,casanova+legrand+quinson.2008.simgrid,casanova+giersch+legrand+al.2014.versatile} is a discrete event simulation framework to study the behavior of large-scale distributed computing platforms as Grids, Peer-to-Peer systems, Clouds and High Performance Computation systems. It is widely used to simulate and evaluate heuristics, prototype applications or even assess legacy MPI applications. It is still actively developed by the scientific community and distributed as an open source software.
 
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@@ -614,15 +615,16 @@ the  network speed  drops down (variation of 12.5\%), the  difference between  t
 \end{figure}
 
 
-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.   In   addition,   it  appears   that  the   Krylov
-multisplitting method tolerates  more the network latency variation  with a less
-rate  increase  of  the  execution   time.   Consequently,  in  the  worst  case
-($lat=6.10^{-5 }$), the  execution time for GMRES is almost  the double than the
-time of the Krylov multisplitting, even  though, the performance was on the same
-order of magnitude with a latency of $8.10^{-6}$.
+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.   In addition,  it  appears that  the
+Krylov multisplitting method tolerates more the network latency variation with a
+less  rate increase  of  the  execution time.\RC{Les  2  prÃ©cÃ©dentes phrases  me
+  semblent en contradiction....}  Consequently, in the worst case ($lat=6.10^{-5
+}$), the  execution time for  GMRES is  almost the double  than the time  of the
+Krylov multisplitting,  even though, the  performance was  on the same  order of
+magnitude with a latency of $8.10^{-6}$.
 
 \subsubsection{Network bandwidth impacts on performance}
 \ \\
@@ -634,7 +636,7 @@ order of magnitude with a latency of $8.10^{-6}$.
  Network & N1 : bw=1Gbs - lat=5.10$^{-5}$ \\ %\hline
  Input matrix size & N$_{x}$ x N$_{y}$ x N$_{z}$ =150 x 150 x 150\\ \hline \\
  \end{tabular}
-\caption{Test conditions: Network bandwidth impacts}
+\caption{Test conditions: Network bandwidth impacts\RC{Qu'est ce qui varie ici? Il n'y a pas de variation dans le tableau}}
 \label{tab:04}
 \end{table}
 
@@ -680,9 +682,9 @@ In these experiments, the input matrix size  has been set from $N_{x} = N_{y}
 time for  both algorithms increases when  the input matrix size  also increases.
 But the interesting results are:
 \begin{enumerate}
-  \item the drastic increase ($10$ times) \RC{Je ne vois pas cela sur la figure}
-\RCE{Corrige} of the  number of  iterations needed  to reach the  convergence for  the classical
-GMRES algorithm when  the matrix size go beyond $N_{x}=150$;
+  \item the drastic increase ($10$ times)  of the number of iterations needed to
+    reach the convergence for the classical GMRES algorithm when the matrix size
+    go beyond $N_{x}=150$; \RC{C'est toujours pas clair... ok le nommbre d'itÃ©rations est 10 fois plus long mais la suite de la phrase ne veut rien dire}
 \item the  classical GMRES execution time  is almost the double  for $N_{x}=140$
   compared with the Krylov multisplitting method.
 \end{enumerate}
