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A domain decomposition method for scattered data approximation on a distributed memory multiprocessor

✍ 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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✦ 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.


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