DocumentCode
3015541
Title
Prioritized Multiplicative Schwarz Procedures for Solving Linear Systems
Author
Wingate, David ; Powell, Nathaniel ; Snell, Quinn ; Seppi, Kevin
Author_Institution
Dept. of Comput. Sci., Brigham Young Univ., Provo, UT, USA
fYear
2005
fDate
04-08 April 2005
Abstract
We describe a new algorithm designed to quickly and robustly solve general linear problems of the form Ax = b. We describe both serial and parallel versions of the algorithm, which can be considered a prioritized version of an Alternating Multiplicative Schwarz procedure. We also adopt a general view of alternating Multiplicative Schwarz procedures which motivates their use on arbitrary problems (even which may not have arisen from problems that are naturally decomposable) by demonstrating that, even in a serial context, algorithms should use many, many partitions to accelerate convergence; having such an over-partitioned system also allows easy parallelization of the algorithm, and scales extremely well. We present extensive empirical evidence which demonstrates that our algorithm, with a companion subsolver, can often improve performance by several orders of magnitude over the subsolver by itself and over other algorithms.
Keywords
iterative methods; parallel algorithms; sparse matrices; algorithm parallelization; iterative methods; linear system; prioritized multiplicative Schwarz procedure; sparse matrices; subsolver; Acceleration; Algorithm design and analysis; Computer science; Convergence; Error correction; Linear systems; Matrix decomposition; Partitioning algorithms; Robustness; Sparse matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International
Print_ISBN
0-7695-2312-9
Type
conf
DOI
10.1109/IPDPS.2005.359
Filename
1419822
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