From: couturie Date: Fri, 8 May 2015 13:42:17 +0000 (+0200) Subject: petites modifs 5.4.2 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/commitdiff_plain/f191ea095298626cf15138076b2e26ee4dec9b15?ds=inline petites modifs 5.4.2 --- diff --git a/paper.tex b/paper.tex index 14147dd..24ddab9 100644 --- a/paper.tex +++ b/paper.tex @@ -574,7 +574,15 @@ The execution times between both algorithms is significant with different grid a \end{figure} \subsubsection{Simulations for two different inter-clusters network speeds\\} -In Figure~\ref{fig:02} we present the execution times of both algorithms to solve a 3D Poisson problem of size $150^3$ on two different simulated network $N1$ and $N2$ (see Table~\ref{tab:01}). As it was previously said, we can see from the figure that the Krylov two-stage algorithm is more sensitive to the number of clusters than the GMRES algorithm. However, we can notice an interesting behavior of the Krylov two-stage algorithm. It is less sensitive to bad network bandwidth and latency for the inter-clusters links than the GMRES algorithms. This means that the multisplitting methods are more efficient for distributed systems with high latency networks. +In Figure~\ref{fig:02} we present the execution times of both algorithms to +solve a 3D Poisson problem of size $150^3$ on two different simulated network +$N1$ and $N2$ (see Table~\ref{tab:01}). As previously mentioned, we can see from +this figure that the Krylov two-stage algorithm is sensitive to the number of +clusters (i.e. it is better to have a small number of clusters). However, we can +notice an interesting behavior of the Krylov two-stage algorithm. It is less +sensitive to bad network bandwidth and latency for the inter-clusters links than +the GMRES algorithms. This means that the multisplitting methods are more +efficient for distributed systems with high latency networks. %% In this section, the experiments compare the behavior of the algorithms running on a %% speeder inter-cluster network (N2) and also on a less performant network (N1) respectively defined in the test conditions Table~\ref{tab:02}.