From e38d4c15dbaa62dc8c0b2e394690e3258b475ba7 Mon Sep 17 00:00:00 2001 From: wolf Date: Wed, 24 Mar 2004 16:32:52 +0000 Subject: [PATCH] More doc updates. git-svn-id: https://svn.dealii.org/trunk@8859 0785d39b-7218-0410-832d-ea1e28bc413d --- .../deal.II/include/dofs/dof_constraints.h | 27 +++++++++++-------- 1 file changed, 16 insertions(+), 11 deletions(-) diff --git a/deal.II/deal.II/include/dofs/dof_constraints.h b/deal.II/deal.II/include/dofs/dof_constraints.h index 6470d056b5..dc98565e07 100644 --- a/deal.II/deal.II/include/dofs/dof_constraints.h +++ b/deal.II/deal.II/include/dofs/dof_constraints.h @@ -69,22 +69,27 @@ class BlockIndices; * applied to matrix and right hand side of the linear system, while the * distribute() function is applied to the solution vector. * - * Condensation is done in four steps: first the large matrix sparsity pattern - * is created (e.g. using @ref{DoFHandler}@p{::create_sparsity_pattern}), then the - * sparsity pattern of the condensed matrix is made out of the large sparsity - * pattern and the constraints. After that the global matrix is assembled and - * finally condensed. To do these steps, you have (at least) two possibilities: + * + * @sect3{Condensing matrices and sparsity patterns} + * + * Condensation of a matrix is done in four steps: first one builds the + * sparsity pattern (e.g. using + * @ref{DoFHandler}@p{::create_sparsity_pattern}); then the sparsity pattern + * of the condensed matrix is made out of the original sparsity pattern and + * the constraints; third, the global matrix is assembled; and fourth, the + * matrix is finally condensed. To do these steps, you have (at least) two + * possibilities: + * * @begin{itemize} * @item Use two different sparsity patterns and two different matrices: you * may eliminate the lines and rows connected with a constraint and create * a totally new sparsity pattern and a new system matrix. This has the - * advantage that the resulting system of equations is free from artifacts - * of the condensation process and is therefore faster in the solution process - * since no unnecessary multiplications occur (see below). However, there are + * advantage that the resulting system of equations is smaller and free from + * artifacts of the condensation process and is therefore faster in the solution + * process since no unnecessary multiplications occur (see below). However, there are * two major drawbacks: keeping two matrices at the same time can be quite - * unacceptable in many cases, since these matrices may be several 10 or even - * 100 MB large. Secondly, the condensation process is quite expensive, since - * all entries of the matrix have to be copied, not only + * unacceptable if you're short of memory. Secondly, the condensation process is + * expensive, since all entries of the matrix have to be copied, not only * those which are subject to constraints. * * @item Use only one sparsity pattern and one matrix: doing it this way, the -- 2.39.5