X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/74d1e243756c3cce524e2fb4f987836574784199..b78099805e44ef25710d8168d3d886021e646084:/hpcc.tex?ds=sidebyside

diff --git a/hpcc.tex b/hpcc.tex
index 5ae025f..28d08c0 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -248,21 +248,27 @@ this paper.  The SMPI interface implements about \np[\%]{80} of the MPI 2.0
 standard~\cite{bedaride:hal-00919507}, and supports applications written in C or
 Fortran, with little or no modifications.
 
-With SimGrid, the execution of a distributed application is simulated on a
+Within SimGrid, the execution of a distributed application is simulated on a
 single machine.  The application code is really executed, but some operations
-like the communications are intercepted to be simulated according to the
-characteristics of the simulated execution platform.  The description of this
-target platform is given as an input for the execution, by the mean of an XML
-file.  It describes the properties of the platform, such as the computing node
-with their computing power, the interconnection links with their bandwidth and
-latency, and the routing strategy.  The simulated running time of the
-application is computed according to these properties.
-
-%%% TODO: add some words+refs about SimGrid's accuracy and scalability.}
-
-\AG{Faut-il ajouter quelque-chose ?} 
-\CER{Comme tu as décrit la plateforme d'exécution, on peut ajouter éventuellement le fichier XML contenant des hosts dans les clusters formant la grille
-  \AG{Bof.}}
+like the communications are intercepted, and their running time is computed
+according to the characteristics of the simulated execution platform.  The
+description of this target platform is given as an input for the execution, by
+the mean of an XML file.  It describes the properties of the platform, such as
+the computing nodes with their computing power, the interconnection links with
+their bandwidth and latency, and the routing strategy.  The simulated running
+time of the application is computed according to these properties.
+
+To compute the durations of the operations in the simulated world, and to take
+into account resource sharing (e.g. bandwidth sharing between competing
+communications), SimGrid uses a fluid model.  This allows to run relatively fast
+simulations, while still keeping accurate
+results~\cite{bedaride:hal-00919507,tomacs13}.  Moreover, depending on the
+simulated application, SimGrid/SMPI allows to skip long lasting computations and
+to only take their duration into account.  When the real computations cannot be
+skipped, but the results have no importance for the simulation results, there is
+also the possibility to share dynamically allocated data structures between
+several simulated processes, and thus to reduce the whole memory consumption.
+These two techniques can help to run simulations at a very large scale.
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \section{Simulation of the multisplitting method}
@@ -372,7 +378,9 @@ Note here that the use of SMPI functions optimizer for memory footprint and CPU
 As mentioned, upon this adaptation, the algorithm is executed as in the real life in the simulated environment after the following minor changes. First, all declared 
 global variables have been moved to local variables for each subroutine. In fact, global variables generate side effects arising from the concurrent access of 
 shared memory used by threads simulating each computing unit in the SimGrid architecture. Second, the alignment of certain types of variables such as ``long int'' had
-also to be reviewed. Finally, some compilation errors on MPI\_Waitall and MPI\_Finalize primitives have been fixed with the latest version of SimGrid.
+also to be reviewed.
+\AG{À propos de ces problèmes d'alignement, en dire plus si ça a un intérêt, ou l'enlever.}
+ Finally, some compilation errors on MPI\_Waitall and MPI\_Finalize primitives have been fixed with the latest version of SimGrid.
 In total, the initial MPI program running on the simulation environment SMPI gave after a very simple adaptation the same results as those obtained in a real 
 environment. We have successfully executed the code in synchronous mode using GMRES algorithm compared with a multisplitting method in asynchrnous mode after few modification. 
 
@@ -441,7 +449,8 @@ containing 50 hosts each, totaling 100 hosts. Various combinations of the above
 factors have providing the results shown in Table~\ref{tab.cluster.2x50} with a
 matrix size ranging from $N_x = N_y = N_z = \text{62}$ to 171 elements or from
 $\text{62}^\text{3} = \text{\np{238328}}$ to $\text{171}^\text{3} =
-\text{\np{5211000}}$ entries.
+\text{\np{5000211}}$ entries.
+\AG{Expliquer comment lire les tableaux.}
 
 % use the same column width for the following three tables
 \newlength{\mytablew}\settowidth{\mytablew}{\footnotesize\np{E-11}}
@@ -532,7 +541,7 @@ relative gains greater than 1 with a matrix size from 62 to 100 elements.
     & \np{E-5} & \np{E-5} & \np{E-5} & \np{E-5} & \np{E-5} & \np{E-5} \\
     \hline
     Relative gain
-    & 1.003    & 1,01     & 1,08     & 0.19     & 1.28     & 1.01 \\
+    & 1.003    & 1.01     & 1.08     & 1.19     & 1.28     & 1.01 \\
     \hline
   \end{mytable}
 \end{table}
@@ -567,6 +576,7 @@ Note that the program was run with the following parameters:
 
 \paragraph*{SMPI parameters}
 
+~\\{}\AG{Donner un peu plus de précisions (plateforme en particulier).}
 \begin{itemize}
 	\item HOSTFILE: Hosts file description.
 	\item PLATFORM: file description of the platform architecture : clusters (CPU power,
@@ -582,11 +592,8 @@ lat latency, \dots{}).
 	\item Maximum number of internal and external iterations;
 	\item Internal and external precisions;
 	\item Matrix size $N_x$, $N_y$ and $N_z$;
-%<<<<<<< HEAD
 	\item Matrix diagonal value: \np{6.0};
 	\item Matrix Off-diagonal value: \np{-1.0};
-%=======
-%>>>>>>> 5fb6769d88c1720b6480a28521119ef010462fa6
 	\item Execution Mode: synchronous or asynchronous.
 \end{itemize}
 
@@ -628,6 +635,8 @@ Table~\ref{tab.cluster.3x67}.
 \LZK{Dans le papier, on compare les deux versions synchrone et asycnhrone du multisplitting. Y a t il des résultats pour comparer gmres parallèle classique avec multisplitting asynchrone? Ca permettra de montrer l'intérêt du multisplitting asynchrone sur des clusters distants}
 \CER{En fait, les résultats ont été obtenus en comparant les temps d'exécution entre l'algo classique GMRES en mode synchrone avec le multisplitting en mode asynchrone, le tout sur un environnement de clusters distants}
 
+\RC{Est ce qu'on sait expliquer pourquoi il y a une telle différence entre les résultats avec 2 et 3 clusters... Avec 3 clusters, ils sont pas très bons... Je me demande s'il ne faut pas les enlever...}
+
 \section{Conclusion}
 The experimental results on executing a parallel iterative algorithm in 
 asynchronous mode on an environment simulating a large scale of virtual