From: raphael couturier Date: Mon, 28 Apr 2014 13:55:22 +0000 (+0200) Subject: Merge branch 'master' of ssh://info.iut-bm.univ-fcomte.fr/hpcc2014 X-Git-Tag: hpcc2014_submission~31 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/commitdiff_plain/51c03eb8a38bbfba54b1e2fadca7ab7b1db166b3?hp=-c Merge branch 'master' of ssh://info.iut-bm.univ-fcomte.fr/hpcc2014 --- 51c03eb8a38bbfba54b1e2fadca7ab7b1db166b3 diff --combined hpcc.tex index 2434416,a5aeb12..7d96f2b --- a/hpcc.tex +++ b/hpcc.tex @@@ -82,8 -82,8 +82,8 @@@ what parameters could influence or no paper, we show that it is interesting to use SimGrid to simulate the behaviors of asynchronous iterative algorithms. For that, we compare the behaviour of a synchronous GMRES algorithm with an asynchronous multisplitting one with - simulations in which we choose some parameters. Both codes are real MPI - codes. Simulations allow us to see when the multisplitting algorithm can be more + simulations which let us easily choose some parameters. Both codes are real MPI + codes ans simulations allow us to see when the asynchronous multisplitting algorithm can be more efficient than the GMRES one to solve a 3D Poisson problem. @@@ -695,11 -695,9 +695,11 @@@ In this work, we show that SIMGRID is a reach the following three objectives: \begin{enumerate} -\item To have a flexible configurable execution platform resolving the -hard exercise to access to very limited but so solicited physical -resources; +\item To have a flexible configurable execution platform that allows us to + simulate asynchronous iterative algorithm for which execution of all parts of + the code is necessary. Using simulations before real execution is a nice + solution to detect the scalability problems. + \item to ensure the algorithm convergence with a reasonable time and iteration number ; \item and finally and more importantly, to find the correct combination