X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/c7b906cdc0242f831963b1079a3bebcfa8ff36b9..9e58442a55b1f2eda6edb277b367dc4e34f1fa1e:/hpcc.tex?ds=sidebyside

diff --git a/hpcc.tex b/hpcc.tex
index affe6f7..b857d5c 100644
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -31,6 +31,8 @@
   \todo[color=blue!10,#1]{\sffamily\textbf{LZK:} #2}\xspace}
 \newcommand{\RC}[2][inline]{%
   \todo[color=red!10,#1]{\sffamily\textbf{RC:} #2}\xspace}
+\newcommand{\CER}[2][inline]{%
+  \todo[color=pink!10,#1]{\sffamily\textbf{CER:} #2}\xspace}
 
 \algnewcommand\algorithmicinput{\textbf{Input:}}
 \algnewcommand\Input{\item[\algorithmicinput]}
@@ -150,7 +152,7 @@ SimGrid toolkit~\cite{SimGrid}). Second, we confirm the effectiveness of
 asynchronous mode algorithms by comparing their performance with the synchronous
 mode. More precisely, we had implemented a program for solving large
 non-symmetric linear system of equations by numerical method GMRES (Generalized
-Minimal Residual) []\AG[]{[]?}. We show, that with minor modifications of the
+Minimal Residual) []\AG[]{[]?}.\LZK{ProblÃ¨me traitÃ© dans le papier est symÃ©trique ou asymÃ©trique? (Poisson 3D symÃ©trique?)} We show, that with minor modifications of the
 initial MPI code, the SimGrid toolkit allows us to perform a test campaign of a
 real AIAC application on different computing architectures. The simulated
 results we obtained are in line with real results exposed in ??\AG[]{??}.
@@ -250,7 +252,8 @@ 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.
 
-\AG{Faut-il ajouter quelque-chose ?}
+\AG{Faut-il ajouter quelque-chose ?} 
+\CER{Comme tu as dÃ©crit la plateforme d'exÃ©cution, on peut ajouter Ã©ventuellement le fichier XML contenant des hosts dans les clusters formant la grille} 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \section{Simulation of the multisplitting method}
@@ -361,13 +364,12 @@ condition is satisfied
 where $\MI$ is the maximum number of outer iterations and $\epsilon$ is the tolerance threshold of the error computed between two successive local solution $X_l^k$ and $X_l^{k+1}$. 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-We did not encounter major blocking problems when adapting the multisplitting algorithm previously described to a simulation environment like SIMGRI\LZK[]{SimGrid} unless some code 
-debugging. Indeed, apart from the review of the program sequence for asynchronous exchanges between the six neighbors of each point in a submatrix within a cluster or 
-between clusters, \LZK{Il faut expliquer pourquoi 6 points voisins (7-point stencil problem)}
+We did not encounter major blocking problems when adapting the multisplitting algorithm previously described to a simulation environment like SimGrid\LZK[]{SimGrid} unless some code 
+debugging. Indeed, apart from the review of the program sequence for asynchronous exchanges between the six neighbors of each point (left,right,front,behind,top,down) in a cubic partitionned submatrix within a cluster or between clusters, \LZK{Il faut expliquer pourquoi 6 points voisins (7-point stencil problem)} \CER{J'ai rajoutÃ© quelques prÃ©cisions mais serait-il nÃ©cessaire de dÃ©crire a ce niveau la discrÃ©tisation 3D ?}
 the algorithm was executed successfully with SMPI and provided identical outputs as those obtained with direct execution under MPI. In synchronous 
 mode, the execution of the program raised no particular issue but in asynchronous mode, the review of the sequence of MPI\_Isend, MPI\_Irecv and MPI\_Waitall instructions
 and with the addition of the primitive MPI\_Test was needed to avoid a memory fault due to an infinite loop resulting from the non-convergence of the algorithm.
-\LZK{Peut-Ãªtre mettre plus de prÃ©cisions sur les difficultÃ©s rencontrÃ©es dans la version async et les adaptaions effectuÃ©es pour SimGrid}
+\LZK{Peut-Ãªtre mettre plus de prÃ©cisions sur les difficultÃ©s rencontrÃ©es dans la version async et les adaptaions effectuÃ©es pour SimGrid}\CER{On voulait en fait montrer la simplicitÃ© de l'adaptation de l'algo a SimGrid. Les problÃ¨mes rencontrÃ©s dÃ©crits dans ce paragraphe concerne surtout le mode async}
 Note here that the use of SMPI functions optimizer for memory footprint and CPU usage is not recommended knowing that one wants to get real results by simulation.
 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 
@@ -375,7 +377,7 @@ shared memory used by threads simulating each computing unit in the SimGrid arch
 also to be reviewed. 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 tested in synchronous mode with a simulated platform starting from a modest 2 or 3 clusters grid to a larger configuration like simulating 
-Grid5000 with more than 1500 hosts with 5000 cores~\cite{bolze2006grid}. Once the code debugging and adaptation were complete, the next section shows our methodology and experimental results.\LZK{DerniÃ¨re phrase peut Ãªtre supprimÃ©e}
+Grid5000 with more than 1500 hosts with 5000 cores~\cite{bolze2006grid}.\LZK{DerniÃ¨re phrase peut Ãªtre supprimÃ©e} \CER {J'ai enlevÃ© la derniÃ¨re phrase}
 
 
 
@@ -413,7 +415,7 @@ 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.
 \LZK{Donner le type et la description du problÃ¨me traitÃ© (problÃ¨me symÃ©trique Poisson 3D) et prÃ©ciser peut Ãªtre aussi qu'on a utilisÃ© un partitionnement 3D}
-
+\CER{Voir ma remarque plus si nÃ©cessaire de dÃ©crire en dÃ©tail le partitionnement 3D}
 % use the same column width for the following three tables
 \newlength{\mytablew}\settowidth{\mytablew}{\footnotesize\np{E-11}}
 \newenvironment{mytable}[1]{% #1: number of columns for data
@@ -553,7 +555,14 @@ lat latency, \dots{}).
 	\item Maximum number of internal and external iterations;
 	\item Internal and external precisions;
 	\item Matrix size $N_x$, $N_y$ and $N_z$;
-	\item Matrix diagonal value: \np{6.0}, \LZK{Off-diagonal values? (-1?)}
+<<<<<<< HEAD
+	\item Matrix diagonal value: \np{6.0};
+	\item Matrix Off-diagonal value: \np{-1};
+	 \LZK{Off-diagonal values? (-1?)}
+	 \CER{oui}
+=======
+	\item Matrix diagonal value: \np{6.0}, \LZK{Off-diagonal values? (-1.0?)}
+>>>>>>> 5fb6769d88c1720b6480a28521119ef010462fa6
 	\item Execution Mode: synchronous or asynchronous.
 \end{itemize}
 
@@ -623,6 +632,8 @@ demonstrated an original solution to optimize the use of a simulation
 tool to run efficiently an iterative parallel algorithm in asynchronous 
 mode in a grid architecture. 
 
+\LZK{Perspectives???}
+
 \section*{Acknowledgment}
 
 This work is partially funded by the Labex ACTION program (contract ANR-11-LABX-01-01).
