MSPAI: Difference between revisions
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== Implementation and Features == | == Implementation and Features == | ||
The entire implementation is done in C++ with parallelization in MPI. Except the Block SPAI approach, we cover the full functionality of SPAI 3.2. | |||
=== Methodical improvements === | |||
* Extension to target form: allow probing | |||
* Support for explicit and inverse approximations, both in factorized and unfactorized form and probing of Schur complements, see [http://www5.in.tum.de/software/mspai/mspai_variants.pdf pdf] | |||
=== Technical improvements === | |||
* Support for complex valued problems | |||
* Support for sparse QR methods using [http://www.cise.ufl.edu/research/sparse/CSparse/ CSparse] by Tim Davis | |||
* Caching approach to avoid redundant QR decompositions | |||
* Implementation of QR updates to accelerate pattern update steps | |||
* Support for maximum sparsity patterns | |||
* Arbitrary start patterns, i.e. possibility to compute a ''static'' SPAI without pattern update steps | |||
=== Todo === | |||
* Mex interface for MATLAB | |||
* PetSc interface | |||
* Support for other LAPACK implementations than ATLAS | |||
* Wider coverage of file formats for sparse matrices, now support for Matrix Market format only | |||
== Download == | == Download == | ||
* MSPAI 1.1 source code tar ball: [] | |||
* MSPAI manual, closely adapted from SPAI 3.2 manual: [] | |||
* Ph.D. thesis about MSPAI, both theory and implementation: [http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:91-diss-20071114-632977-1-5 mediatum] | * Ph.D. thesis about MSPAI, both theory and implementation: [http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:91-diss-20071114-632977-1-5 mediatum] |
Revision as of 20:09, 20 September 2008
Modified Sparse Approximate Inverses -- UNDER CONSTRUCTION!!!
Based upon the well-known sparse approximate inverse preconditioner SPAI, we developed the modified sparse approximate inverse (MSPAI) preconditioner.
Theory
MSPAI is a preconditioner for large sparse and ill-conditioned systems of linear equations. We extended the basic SPAI minimization
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to target form and further generalized it in order to add additional probing constraints:
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For an overview of the versatile employment possibilities of our MSPAI formulation, see this pdf taken from here.
Implementation and Features
The entire implementation is done in C++ with parallelization in MPI. Except the Block SPAI approach, we cover the full functionality of SPAI 3.2.
Methodical improvements
- Extension to target form: allow probing
- Support for explicit and inverse approximations, both in factorized and unfactorized form and probing of Schur complements, see pdf
Technical improvements
- Support for complex valued problems
- Support for sparse QR methods using CSparse by Tim Davis
- Caching approach to avoid redundant QR decompositions
- Implementation of QR updates to accelerate pattern update steps
- Support for maximum sparsity patterns
- Arbitrary start patterns, i.e. possibility to compute a static SPAI without pattern update steps
Todo
- Mex interface for MATLAB
- PetSc interface
- Support for other LAPACK implementations than ATLAS
- Wider coverage of file formats for sparse matrices, now support for Matrix Market format only
Download
- MSPAI 1.1 source code tar ball: []
- MSPAI manual, closely adapted from SPAI 3.2 manual: []
- Ph.D. thesis about MSPAI, both theory and implementation: mediatum
- Details about sparse QR methods in SPAI applications (german only): []
- Further details about implementation (german only): pdf
MSPAI References
<pubsccs>nocaption=1&persid=53&utypid=1020&datum=2007&lang=en</pubsccs><pubsccs>nocaption=1&persid=53&utypid=2030&datum=2008&lang=en</pubsccs>
under construction -- more information about MSPAI implementation and download will be available soon.