From: David Laiymani Date: Tue, 29 Apr 2014 12:29:53 +0000 (+0200) Subject: modifs intro + conclu X-Git-Tag: hpcc2014_submission~7 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/commitdiff_plain/0ed25093da14942800a6808b24fe51623cb882d3?ds=inline;hp=d0df474d3df1a66a6e43d1513fc3e9ed1248d2ed modifs intro + conclu --- diff --git a/hpcc.tex b/hpcc.tex index 22fa047..6e262b1 100644 --- a/hpcc.tex +++ b/hpcc.tex @@ -162,7 +162,8 @@ network platforms are the bandwidth and the latency of inter cluster network. Parameters on the cluster's architecture are the number of machines and the computation power of a machine. Simulations show that the asynchronous multisplitting algorithm can solve the 3D Poisson problem approximately twice -faster than GMRES with two distant clusters. +faster than GMRES with two distant clusters. In this way, we present an original solution to optimize the use of a simulation +tool to run efficiently an asynchronous iterative parallel algorithm in a grid architecture @@ -661,8 +662,8 @@ the results have given a relative gain more than 2.5, showing the effectiveness asynchronous multisplitting compared to GMRES with two distant clusters. With these settings, Table~\ref{tab.cluster.2x50} shows -that after setting the bandwidth of the inter cluster network to \np[Mbit/s]{5} and a latency in order of one hundredth of millisecond and a processor power -of one GFlops, an efficiency of about \np[\%]{40} is +that after setting the bandwidth of the inter cluster network to \np[Mbit/s]{5}, the latency to $20$ millisecond and the processor power +to one GFlops, an efficiency of about \np[\%]{40} is obtained in asynchronous mode for a matrix size of $62^3$ elements. It is noticed that the result remains stable even we vary the residual error precision from \np{E-5} to \np{E-9}. By increasing the matrix size up to $100^3$ elements, it was necessary to increase the @@ -692,7 +693,7 @@ 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. -In this work, we show that SIMGRID is an efficient simulation tool that allows us to +In this work, we show that SimGrid is an efficient simulation tool that allows us to reach the following two objectives: \begin{enumerate}