From cce18db44812b9a67dd4d30ca37ea74fd46f16b1 Mon Sep 17 00:00:00 2001 From: raphael couturier Date: Sun, 12 Oct 2014 08:12:12 +0200 Subject: [PATCH] new --- paper.tex | 24 +++++++++++++++++++----- 1 file changed, 19 insertions(+), 5 deletions(-) diff --git a/paper.tex b/paper.tex index 32e9a3f..cf61a9e 100644 --- a/paper.tex +++ b/paper.tex @@ -1106,11 +1106,25 @@ taken into account with TSIRM. \end{figure} -Concerning the experiments some other remarks are interesting. We can tested -other examples of PETSc (ex29, ex45, ex49). For all these examples, we also -obtained similar gain between GMRES and TSIRM but those examples are not -scalable with many cores. In general, we had some problems with more than -$4,096$ cores. +Concerning the experiments some other remarks are interesting. +\begin{itemize} +\item We can tested other examples of PETSc (ex29, ex45, ex49). For all these + examples, we also obtained similar gain between GMRES and TSIRM but those + examples are not scalable with many cores. In general, we had some problems + with more than $4,096$ cores. +\item We have tested many iterative solvers available in PETSc. In fast, it is + possible to use most of them with TSIRM. From our point of view, the condition + to use a solver inside TSIRM is that the solver must have a restart + feature. More precisely, the solver must support to be stoped and restarted + without decrease its converge. That is why with GMRES we stop it when it is + naturraly restarted (i.e. with $m$ the restart parameter). The Conjugate + Gradient (CG) and all its variants do not have ``restarted'' version in PETSc, + so they are not efficient. They will converge with TSIRM but not quickly + because if we compare a normal CG with a CG for which we stop it each 16 + iterations for example, the normal CG will be for more efficient. Some + restarted CG or CG variant versions exist and may be interested to study in + future works. +\end{itemize} %%%********************************************************* %%%********************************************************* -- 2.39.5