• Numerical performance of preco...

Result: Numerical performance of preconditioning techniques for the solution of complex sparse linear systems

Title:
Numerical performance of preconditioning techniques for the solution of complex sparse linear systems
Authors:
MAZZIA, ANNAMARIA, PINI, GIORGIO
Source:
Communications in Numerical Methods in Engineering. 19:37-48
Publisher Information:
Wiley, 2002.
Publication Year:
2002
Subject Terms:
Iterative numerical methods for linear systems, Numerical computation of matrix norms, conditioning, scaling, parallel algorithms, Parallel numerical computation, preconditioned iterative methods, sparse approximate inverse, 01 natural sciences, Computational methods for sparse matrices, Complexity and performance of numerical algorithms, Frobenius norm minimization, preconditioning, approximate inverses, complex sparse linear systems, preconditioned iterative methods, incomplete factorizations, approximate inverses, parallel algorithms, ILU decomposition, conjugate gradient-type methods, incomplete factorizations, 0101 mathematics, numerical experiments, complex sparse linear systems
Document Type:
Academic journal Article
File Description:
application/xml
Language:
English
ISSN:
1099-0887
1069-8299
DOI:
10.1002/cnm.568
Access URL:
https://zbmath.org/1872739
https://doi.org/10.1002/cnm.568
http://onlinelibrary.wiley.com/doi/10.1002/cnm.568/abstract
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fcnm.568
https://hdl.handle.net/11577/2461521
Rights:
Wiley Online Library User Agreement
Accession Number:
edsair.doi.dedup.....e11248d0639bb546b69bffc1cd67c9f3
Database:
OpenAIRE

Further Information

Preconditioning techniques based on ILU decomposition, on Frobenius norm minimization and on factorized sparse approximate inverse are considered. These algorithms are applied with conjugate gradient‐type methods, namely Bi‐CGSTAB, QMR and TFQMR for the solution of complex, large, sparse linear systems. The results of numerical experiments in scalar environment with matrices arising from transport in porous media, quantum chemistry, structural dynamics and electromagnetism are analysed. The preconditioner that appears most significant in parallel environment (based on factorized sparse approximate inverse) is then employed on a Cray T3E supercomputer. The experimental results show the satisfactory parallel performance of the proposed algorithm. Copyright © 2003 John Wiley & Sons, Ltd.