Conjugate gradient methods for solving sparse systems of linear equations and Lanczos algorithms for sparse symmetric eigenvalue problems play an important role in numerical methods for solving discretized partial differential equations. When these iterative solvers are parallelized on a multiproces
A preconditioned Conjugate Gradient Method on a distributed memory multiprocessor
โ Scribed by R. Bru; C. Corral; J. Mas
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 279 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0893-9659
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โฆ Synopsis
This paper discusses preconditioners for the Conjugate Gradient Method which are based on splittings of the system matrix. Conditions for the convergence are given, and particular splittings are chosen in order to implement the method on a distributed memory multiprocessor.
๐ SIMILAR VOLUMES
Bacchelli Montefusco, L. and C. Guerrini, A domain decomposition method for scattered data approximation on a distributed memory multiprocessor, Parallel Computing 17 (1991) 253-263 The problem of reconstructing a function f(x, y) from N experimental evaluations (xi, Yi, f/), i = 1 ..... N irregular