X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/7845b6502c9948b08bc33b38b0ac5293125e565e..108b6ffda00e3d8bf697f0f6ee88c0c6e9d53e3f:/hpcc.tex?ds=inline

diff --git a/hpcc.tex b/hpcc.tex
index b2509c1..6a39362 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -232,9 +232,9 @@ asynchronous iterative algorithms comes from the fact it is necessary to run the
 with real data. In fact, from an execution to another the order of messages will
 change and the  number of iterations to reach the  convergence will also change.
 According  to all  the parameters  of the  platform (number  of nodes,  power of
-nodes,  inter  and  intra clusrters  bandwith  and  latency,  ....) and  of  the
-algorithm  (number   of  splitting  with  the   multisplitting  algorithm),  the
-multisplitting code  will obtain the solution  more or less  quickly. Or course,
+nodes,  inter  and  intra clusrters  bandwith  and  latency, etc.) and  of  the
+algorithm  (number   of  splittings  with  the   multisplitting  algorithm),  the
+multisplitting code  will obtain the solution  more or less  quickly. Of course,
 the GMRES method also depends of the same parameters. As it is difficult to have
 access to  many clusters,  grids or supercomputers  with many  different network
 parameters,  it  is  interesting  to  be  able  to  simulate  the  behaviors  of
@@ -251,8 +251,8 @@ SimGrid~\cite{SimGrid,casanova+legrand+quinson.2008.simgrid} is a simulation
 framework to study the behavior of large-scale distributed systems.  As its name
 says, it emanates from the grid computing community, but is nowadays used to
 study grids, clouds, HPC or peer-to-peer systems.  The early versions of SimGrid
-date from 1999, but it's still actively developed and distributed as an open
-source software.  Today, it's one of the major generic tools in the field of
+date from 1999, but it is still actively developed and distributed as an open
+source software.  Today, it is one of the major generic tools in the field of
 simulation for large-scale distributed systems.
 
 SimGrid provides several programming interfaces: MSG to simulate Concurrent
@@ -383,8 +383,8 @@ exchanged by message passing using MPI non-blocking communication routines.
 
 \begin{figure}[!t]
 \centering
-  \includegraphics[width=60mm,keepaspectratio]{clustering2}
-\caption{Example of two distant clusters of processors.}
+  \includegraphics[width=60mm,keepaspectratio]{clustering}
+\caption{Example of three distant clusters of processors.}
 \label{fig:4.1}
 \end{figure}
 
@@ -422,7 +422,7 @@ u =0 \text{~on~} \Gamma =\partial\Omega
 \right.
 \label{eq:02}
 \end{equation}
-where $\nabla^2$ is the Laplace operator, $f$ and $u$ are real-valued functions, and $\Omega=[0,1]^3$. The spatial discretization with a finite difference scheme reduces problem~(\ref{eq:02}) to a system of sparse linear equations. Our multisplitting method solves the 3D Poisson problem using a seven point stencil whose the general expression could be written as
+where $\nabla^2$ is the Laplace operator, $f$ and $u$ are real-valued functions, and $\Omega=[0,1]^3$. The spatial discretization with a finite differences scheme reduces problem~(\ref{eq:02}) to a system of sparse linear equations. Our multisplitting method solves the 3D Poisson problem using a seven point stencil whose the general expression could be written as
 \begin{equation}
 \begin{array}{l}
 u(x-1,y,z) + u(x,y-1,z) + u(x,y,z-1)\\+u(x+1,y,z)+u(x,y+1,z)+u(x,y,z+1) \\ -6u(x,y,z)=h^2f(x,y,z),