An iterative solver template library for DUNE

Edit Package dune-istl

dune-istl is the iterative solver template library which provides generic sparse matrix/vector classes and a variety of solvers based on these classes. A special feature is the use of templates to exploit the recursive block structure of finite element matrices at compile time. Available solvers include Krylov methods, (block-) incomplete decompositions and
aggregation-based algebraic multigrid.

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Source Files
Filename Size Changed
dune-istl-2.10.0.tar.gz 0000431967 422 KB
dune-istl.changes 0000006131 5.99 KB
dune-istl.spec 0000004872 4.76 KB
Latest Revision
Dmitry Roshchin's avatar Dmitry Roshchin (Dmitry_R) accepted request 1221877 from Christoph G's avatar Christoph G (mathletic) (revision 17)
- update to version 2.10.0
  * Improve testing support on Laplacian matrices with an optional
    diagonal regularization parameter.
  * Base the implementation of VariableBlockVector on std::vector
    as the storage type. Note that this prevents from using bool
    as block type that was possible before.
  * A method BCRSMatrix::setIndicesNoSort() was added. Similar
    to BCRSMatrix::setIndices() this allows to insert all indices
    of a row at once, but - in contrast to the latter - does not
    sort them. This allows to speed up insertion if indices are
    already sorted.
  * UMFPACK is extended to arbitrary blocked matrix structures.
    This includes MultiTypeBlockMatrix. The external interface
    is unchanged.
  * The internal storage in MatrixIndexSet was changed from
    std::set to a sorted std::vector to improve performance. The
    stored index type was changed from std::size_t to uint32_t to
    reduce memory consumption and improve performance. Hence,
    MatrixIndexSet can no longer be used for very large matrices
    with more than 2^32 columns.
  * Added flag 'useFixedOrder' to the coarsen method of AMGs
    ParallelIndicesCoarsener. If set to true, during the creation
    of the coarser matrix (by accumulation and restriction
    to fewer processes) the coarse matrix rows are ordered in a
    fixed manner, making parallel runs reproducible; the runtime
    is possibly not ideal though.
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