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.
A domain decomposition method for scattered data approximation on a distributed memory multiprocessor
β Scribed by L. Bacchelli Montefusco; C. Guerrini
- Publisher
- Elsevier Science
- Year
- 1991
- Tongue
- English
- Weight
- 456 KB
- Volume
- 17
- Category
- Article
- ISSN
- 0167-8191
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β¦ Synopsis
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 irregularly distributed in the plane, has been considered for very large values of N. In this case the known local methods give the best sequential algorithms, but are not well suited for parallel implementation due to their excessively large arithmetic overhead. In this work we present a domain decomposition parallel method, especially studied for distributed memory multiprocessors which also achieves high efficiency as a sequential algorithm. In fact, it is based on the decomposition strategy already used in the local methods, but a particular decomposition in slightly overlapping regions and appropriate choice of the limited support weight functions has been realized in order to reduce arithmetic, communication and synchronization overheads. A good performance of the coarse grained parallel algorithm is then achieved by means of a dynamic arithmetic load-balance. Timings and efficiency results from a large experimentation carried out on a Hypercube iPSC/2 are given.
π SIMILAR VOLUMES
Wright K., Parallel algorithms for QR decomposition on a shared memory multiprocessor, Parallel Computing 17 (1991) 779-790. Various parallel implementations of algorithms for the QR decomposition of a matrix are compared using shared memory multiprocessors. Algorithms based on both Givens and Hous
## Abstract The partial basic solution vector based domain decomposition method (PBSVβDDM) is well suited for solving largeβscale finite periodic electromagnetic problems.In this work, a new implementation scheme is developed to improve the efficiency of the PBSVβDDM. A set of orthogonal polynomial