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Fast Parallel Finite Element Approximate Inverses

G.A. Gravvanis, K.M. Giannoutakis1
Department of Electrical and Computer Engineering, School of Engineering, Democritus University of Thrace, 12, Vas. Sofias street, GR 671 00 Xanthi, Greece; Email:{ggravvan; kgiannou}

Computer Modeling in Engineering & Sciences 2008, 32(1), 35-44.


A new parallel normalized optimized approximate inverse algorithm, based on the concept of the ``fish bone'' computational approach with cyclic distribution of the processors 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.


Sparse linear systems, preconditioning, parallel normalized approximate inverses, parallel preconditioned conjugate gradient method, parallel computations, symmetric multiprocessor systems, OpenMP.

Cite This Article

Gravvanis, G., Giannoutakis, K. (2008). Fast Parallel Finite Element Approximate Inverses. CMES-Computer Modeling in Engineering & Sciences, 32(1), 35–44.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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