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Modifying CLJP to select grid hierarchies with lower operator complexities and better performance
Author(s) -
Alber David M.
Publication year - 2006
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.473
Subject(s) - multigrid method , polygon mesh , grid , computer science , selection (genetic algorithm) , discretization , operator (biology) , mathematical optimization , algorithm , mathematics , theoretical computer science , partial differential equation , machine learning , mathematical analysis , biochemistry , chemistry , computer graphics (images) , geometry , repressor , transcription factor , gene
Abstract Algebraic multigrid (AMG) is an efficient algorithm for solving certain types of large, sparse linear systems. For solving very large problems with AMG it becomes necessary to use parallel algorithms. Coarse grid selection algorithms such as CLJP were created to parallelize the setup phase of AMG. For some problems, such as those discretized on structured meshes, CLJP tends to select coarse grids with more nodes than alternative coarsening algorithms. In this paper, the cause for the selection of too many coarse nodes by CLJP is examined, and a new technique which lowers the operator complexities generated by CLJP is introduced. To validate the new method, the modified CLJP is compared to other coarsening algorithms for large‐scale problems. Copyright © 2006 John Wiley & Sons, Ltd.