Decomposition Models of Parallel Algorithms

Evaluation of Parallel Domain Decomposition Algorithms

In this talk we describe and evaluate several heuristics for the parallel decomposition of data into n processors. This problem is usually cast as a graph partitioning problem, requiring that each processor have equal amount of data, and that inter-processor communication be minimized. Since this problem is NP-complete, several heuristics have been developed: combinatorial, geometric, spectral,...

Parallel Algorithms for the Singular Value Decomposition

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Parallel Domain Decomposition and Iterativerefinement Algorithms

Algorithms for the solution of partial diierential equations based on a subdivision of the spatial domain, has received much interest in recent years. To a large extent this has been motivated by the new generation of parallel computers. This algorithmic approach can introduce independent parallel tasks of variable granularity, depending on the subdivision and can therefore be adapted to a wide...

Biconjugate Decomposition Using ABS Algorithms

Markov chain models of parallel genetic algorithms

Implementations of parallel genetic algorithms (GAs) with multiple populations are common, but they introduce several parameters whose effect on the quality of the search is not well understood. Parameters such as the number of populations, their size, the topology of communications, and the migration rate have to be set carefully to reach adequate solutions. This paper presents models that pre...