High performance finite element approximate inverse preconditioning

Konstantinos M. Giannoutakis

doi:10.1016/j.amc.2007.12.023

2008-07-01

PRE

Konstantinos M. Giannoutakis

George A. Gravvanis *

DOI：10.1016/j.amc.2007.12.023

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摘要

En 中文

A new parallel normalized optimized approximate inverse algorithm, based on the concept of the fish bone computational approach satisfying an antidiagonal data dependency, for computing classes of explicit approximate inverses, is introduced for symmetric multiprocessor systems. The parallel normalized explicit approximate inverses are used in conjunction with parallel normalized explicit preconditioned conjugate gradient square schemes, for the efficient solution of finite element sparse linear systems. The parallel design and implementation issues of the new proposed algorithms are discussed and the parallel performance is presented, using OpenMP. (c) 2007 Elsevier Inc. All rights reserved.

Keyword:

algorithm design and analysis

concurrent programming

numerical algorithms and problems

sparse linear systems

iterative solution techniques

parallel algorithms

parallelism and concurrency