From: lilia Date: Thu, 9 Jan 2014 22:04:36 +0000 (+0100) Subject: 09-01-2014 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/Krylov_multi.git/commitdiff_plain/3933b25f95c0d8f65bfd2778425ac43c3ed67f20 09-01-2014 --- diff --git a/krylov_multi.tex b/krylov_multi.tex index 91e4745..48d9e2e 100644 --- a/krylov_multi.tex +++ b/krylov_multi.tex @@ -89,12 +89,13 @@ v_l^k=M^{-1}_l N_l x_l^{k-1} + M^{-1}_l b,~l\in\{1,\ldots,L\}, \label{eq04} \end{equation} to be solved independently by a direct or an iterative method, where -$v_l^k$ is the solution of the local sub-system. A multisplitting -method using an iterative method for solving the $L$ linear -sub-systems is called an inner-outer iterative method or a two-stage -method. The results $v_l^k$ obtained from the different -splittings~(\ref{eq04}) are combined to compute the solution $x^k$ of -the linear system by using the diagonal weighting matrices +$v_l^k$ is the solution of the local sub-system. Thus, the +calculations of $v_l^k$ may be performed in parallel by a set of +processors. A multisplitting method using an iterative method for +solving the $L$ linear sub-systems is called an inner-outer iterative +method or a two-stage method. The results $v_l^k$ obtained from the +different splittings~(\ref{eq04}) are combined to compute the solution +$x^k$ of the linear system by using the diagonal weighting matrices \begin{equation} x^k = \displaystyle\sum^L_{l=1} E_l v_l^k, \label{eq05} @@ -160,7 +161,7 @@ b & = & [B_{1}, \ldots, B_{L}] \right. \label{sec03:eq01} \end{equation} -where for all $l\in\{1,\ldots,L\}$ $A_l$ is a rectangular block of size $n_l\times n$ +where for $l\in\{1,\ldots,L\}$ $A_l$ is a rectangular block of size $n_l\times n$ and $X_l$ and $B_l$ are sub-vectors of size $n_l$, such that $\sum_ln_l=n$. In this case, we use a row-by-row splitting without overlapping in such a way that successive rows of the sparse matrix $A$ and both vectors $x$ and $b$ are assigned to one cluster. @@ -186,10 +187,10 @@ Y_l = B_l - \displaystyle\sum_{i=1,i\neq l}^{L}A_{li}X_i, \end{equation} is solved independently by a cluster of processors and communication are required to update the right-hand side vectors $Y_l$, such that the vectors $X_i$ represent the data -dependencies between the clusters. In this case, the parallel GMRES method is used -as an inner iteration method for solving the linear sub-systems~(\ref{sec03:eq03}). - - +dependencies between the clusters. In this work, we use the GMRES method as an inner +iteration method for solving the sub-systems~(\ref{sec03:eq03}). It is a well-known +iterative method which gives good performances for solving sparse linear systems in +parallel on a cluster of processors.