From de1136ccefae31eda903086fc7310086c7a0ed57 Mon Sep 17 00:00:00 2001 From: asider Date: Sun, 17 Jan 2016 21:04:17 +0100 Subject: [PATCH] =?utf8?q?une=20contrib=20=C3=A0=20signaler?= MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit --- paper.tex | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/paper.tex b/paper.tex index 9733c3d..2d47f22 100644 --- a/paper.tex +++ b/paper.tex @@ -109,7 +109,8 @@ In this paper we propose the parallelization of Ehrlich-Aberth method which has \item The parallel implementation of Ehrlich-Aberth algorithm on a multi-GPU platform with a distributed memory using MPI API, such that each GPU is attached and managed by a MPI process. The GPUs exchange their data by message-passing communications. \end{itemize} This latter approach is more used on clusters to solve very complex problems that are too large for traditional supercomputers, which are very expensive to build and run. -\LZK{Pas d'autres contributions possibles? J'ai supprimé les deux premiers points proposés précédemment.} +\LZK{Pas d'autres contributions possibles? J'ai supprimé les deux premiers points proposés précédemment. +\AS{La résolution du problème pour des polynomes pleins de degré 6M est une contribution aussi à mon avis}} The paper is organized as follows. In Section~\ref{sec2} we present three different parallel programming models OpenMP, MPI and CUDA. In Section~\ref{sec3} we present the implementation of the Ehrlich-Aberth algorithm on a single GPU. In Section~\ref{sec4} we present the parallel implementations of the Ehrlich-Aberth algorithm on multiple GPUs using the OpenMP and MPI approaches. In section~\ref{sec5} we present our experiments and discuss them. Finally, Section~\ref{sec6} concludes this paper and gives some hints for future research directions in this topic. -- 2.39.5