Sisyphus repository
Last update: 1 october 2023 | SRPMs: 18631 | Visits: 37037120
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S:3.2-alt9
5.0: 3.2-alt0.M50.1

Group :: Sciences/Mathematics
RPM: spai

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Current version: 3.2-alt9
Build date: 22 september 2021, 14:38 ( 131.1 weeks ago )
Size: 675.35 Kb

Home page:   http://www.computational.unibas.ch/software/spa…

License: GPLv2
Summary: SParse Approximate Inverse Preconditioner
Description:

Given a sparse matrix A the SPAI Algorithm computes a sparse approximate inverse
M by minimizing || AM - I || in the Frobenius norm. The approximate inverse is
computed explicitly and can then be applied as a preconditioner to an iterative
method. The sparsity pattern of the approximate inverse is either fixed a priori
or captured automatically:

 * Fixed sparsity: The sparsity pattern of M is either banded or a subset of
 the sparsity pattern of A.
 * Adaptive sparsity: The algorithm proceeds until the 2-norm of each column of
 AM-I is less than eps. By varying eps the user controls the quality and the
 cost of computing the preconditioner. Usually the optimal eps lies between 0.5
 and 0.7.

A very sparse preconditioner is very cheap to compute but may not lead to much
improvement, while if M becomes rather dense it becomes too expensive to
compute. The optimal preconditioner lies between these two extremes and is
problem and computer architecture dependent.

The approximate inverse M can also be used as a robust (parallel) smoother for
(algebraic) multi-grid methods.

Current maintainer: Eugeny A. Rostovtsev (REAL)

List of contributors

List of rpms provided by this srpm:

  • libspai
  • libspai-debuginfo
  • libspai-devel
  • libspai-devel-doc
  • spai
  • spai-debuginfo
ACL:
     
    design & coding: Vladimir Lettiev aka crux © 2004-2005, Andrew Avramenko aka liks © 2007-2008
    current maintainer: Michael Shigorin