X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/blobdiff_plain/a7a6058c1e5c69798acc7db34e255be4cb545381..0e6d063a9e15647ffb71be54897a88cbe7c9a5b4:/hpcc.tex diff --git a/hpcc.tex b/hpcc.tex index ca655bc..c79ed41 100644 --- a/hpcc.tex +++ b/hpcc.tex @@ -395,9 +395,9 @@ processor is designated (for example the processor with rank 1) and masters of all clusters are interconnected by a virtual unidirectional ring network (see Figure~\ref{fig:4.1}). During the resolution, a Boolean token circulates around the virtual ring from a master processor to another until the global convergence -is achieved. So starting from the cluster with rank 1, each master processor $i$ +is achieved. So starting from the cluster with rank 1, each master processor $\ell$ sets the token to \textit{True} if the local convergence is achieved or to -\textit{False} otherwise, and sends it to master processor $i+1$. Finally, the +\textit{False} otherwise, and sends it to master processor $\ell+1$. Finally, the global convergence is detected when the master of cluster 1 receives from the master of cluster $L$ a token set to \textit{True}. In this case, the master of cluster 1 broadcasts a stop message to masters of other clusters. In this work, @@ -691,7 +691,7 @@ elements. %\CER{Définitivement, les paramètres réseaux variables ici se rapportent au réseau INTER cluster.} \section{Conclusion} The simulation of the execution of parallel asynchronous iterative algorithms on large scale clusters has been presented. -Our work has demonstrated that using such a simulation tool allow us to +In this work, we show that SIMGRID is an efficient simulation tool that allows us to reach the following three objectives: \begin{enumerate} @@ -705,17 +705,18 @@ of the cluster and network specifications permitting to save time in executing the algorithm in asynchronous mode. \end{enumerate} Our results have shown that in certain conditions, asynchronous mode is -speeder up to \np[\%]{40} than executing the algorithm in synchronous mode +speeder up to \np[\%]{40} comparing to the synchronous GMRES method which is not negligible for solving complex practical problems with more and more increasing size. - Several studies have already addressed the performance execution time of +Several studies have already addressed the performance execution time of this class of algorithm. The work presented in this paper has 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???} +For our futur works, we plan to extend our experimentations to larger scale platforms by increasing the number of computing cores and the number of clusters. +We will also have to increase the size of the input problem which will require the use of a more powerful simulation platform. At last, we expect to compare our simulation results to real execution results on real architectures in order to experimentally validate our study. \section*{Acknowledgment}