From 1e2fbfd32f825b023fdc9af78a0565ba2ae93a6c Mon Sep 17 00:00:00 2001 From: raphael couturier Date: Wed, 9 Apr 2014 20:33:12 +0200 Subject: [PATCH 1/1] new --- krylov_multi.tex | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/krylov_multi.tex b/krylov_multi.tex index 7a7e809..6e1f16c 100644 --- a/krylov_multi.tex +++ b/krylov_multi.tex @@ -5,6 +5,7 @@ \usepackage{graphicx} \usepackage{algorithm} \usepackage{algpseudocode} +\usepackage{multirow} \algnewcommand\algorithmicinput{\textbf{Input:}} \algnewcommand\Input{\item[\algorithmicinput]} @@ -12,6 +13,9 @@ \algnewcommand\algorithmicoutput{\textbf{Output:}} \algnewcommand\Output{\item[\algorithmicoutput]} +\newcommand{\Time}[1]{\mathit{Time}_\mathit{#1}} +\newcommand{\Prec}{\mathit{prec}} +\newcommand{\Ratio}{\mathit{Ratio}} \title{A scalable multisplitting algorithm for solving large sparse linear systems} \date{} @@ -352,6 +356,30 @@ obtained for a 3D Poisson problem, the number of iterations is high. Using a preconditioner it is possible to reduce the number of iterations but preconditioners are not scalable when using many cores. +Doing many experiments with many cores is not easy and require to access to a +supercomputer with several hours for developping a code and then improving +it. In the following we presented some experiments we could achieved out on the +Hector architecture, the previous UK's high-end computing resource, funded by +the UK Research Councils, which has been stopped in the early 2014. + +In the experiments we report the size of the 3D poisson considered, the number +of processors used (with the decomposition for the multisplitting), the number +of iterations for the GMRES method and the krylov multisplitting one and finally +the execution times. We also give the other parameters: the restart for the +GRMES method + + +\begin{table}[p] +\begin{center} +\begin{tabular}{|c||c|c|} +\hline +Problem size & +\end{tabular} +\caption{CAPTION} +\label{tab1} +\end{center} +\end{table} + \section{Conclusion and perspectives} Other applications (=> other matrices)\\ -- 2.39.5