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| author | B. Watson <yalhcru@gmail.com> | 2020-10-11 15:35:52 -0400 |
|---|---|---|
| committer | Willy Sudiarto Raharjo <willysr@slackbuilds.org> | 2020-10-17 09:36:37 +0700 |
| commit | a37908e881a0fcf2aef608cacbccbb2954ab36eb (patch) | |
| tree | 498b0c2e4642f7947b9928027b0e7f182bf27951 /academic/PyAMG | |
| parent | a9e9805cf5780070c4117217e08f8c93323d0acf (diff) | |
academic/PyAMG: Fix README.
Signed-off-by: B. Watson <yalhcru@gmail.com>
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
Diffstat (limited to 'academic/PyAMG')
| -rw-r--r-- | academic/PyAMG/README | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/academic/PyAMG/README b/academic/PyAMG/README index c72262fa351c..f5a2ac3fe5d9 100644 --- a/academic/PyAMG/README +++ b/academic/PyAMG/README @@ -1,9 +1,9 @@ -PyAMG is a library of **Algebraic Multigrid (AMG)** solvers with a convenient -Python interface. +PyAMG is a library of **Algebraic Multigrid (AMG)** solvers with a +convenient Python interface. -AMG is a multilevel technique for solving large-scale linear systems with -optimal or near-optimal efficiency. Unlike geometric multigrid, AMG requires -little or no geometric information about the underlying problem and develops a -sequence of coarser grids directly from the input matrix. This feature is -especially important for problems discretized on unstructured meshes and -irregular grids. +AMG is a multilevel technique for solving large-scale linear systems +with optimal or near-optimal efficiency. Unlike geometric multigrid, +AMG requires little or no geometric information about the underlying +problem and develops a sequence of coarser grids directly from the +input matrix. This feature is especially important for problems +discretized on unstructured meshes and irregular grids. |