From: asider Date: Fri, 15 Jan 2016 20:41:15 +0000 (+0100) Subject: modif commentaire fig 9 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/kahina_paper2.git/commitdiff_plain/4db665ef149942bc02e41b0556b37ccb0a072955?ds=sidebyside;hp=--cc modif commentaire fig 9 --- 4db665ef149942bc02e41b0556b37ccb0a072955 diff --git a/paper.tex b/paper.tex index e826d2d..25a169d 100644 --- a/paper.tex +++ b/paper.tex @@ -1099,11 +1099,12 @@ sparse and full polynomials ranging from 1,000,000 to 5,000,000. \label{fig:09} \end{figure} In Figure~\ref{fig:09} we can see that both approaches are scalable -and can solve very high degree polynomials. With full polynomial both -approaches give very similar results. However, for sparse polynomials -there are a noticeable difference in favour of MPI when the degree is -above 4 millions. Between 1 and 3 millions, OpenMP is more effecient. -Under 1 million, OpenMPI and MPI are almost equivalent. +and can solve very high degree polynomials. In addition, with full polynomial as well as sparse ones, both +approaches give very similar results. + +%SIDER JE viens de virer \c ca For sparse polynomials here are a noticeable difference in favour of MPI when the degree is +%above 4 millions. Between 1 and 3 millions, OpenMP is more effecient. +%Under 1 million, OpenMPI and MPI are almost equivalent. %SIDER : il faut une explication sur les différences ici aussi.