Randomized fully-scalable BSP techniques for multi-searching and convex hull construction
- Johns Hopkins Univ., Baltimore, MD (United States)
We study randomized techniques for designing efficient algorithms on a p-processor bulk-synchronous parallel (BSP) computer, which is a parallel multicomputer that allows for general processor-to-processor communication rounds provided each processor is guaranteed to send and receive at most h items in any round. The measure of efficiency we use is in terms of the internal computation time of the processors and the number of communication rounds needed to solve the problem at hand. We present techniques that achieve optimal efficiency in these bounds over all possible values for p, and we call such techniques fully-scalable for this reason. In particular, we address two fundamental problems: multi-searching and convex hull construction. Our methods result in algorithms that use internal time that is O(n log n/p) and, for h = {Theta}(n/p), a number of communication rounds that is O(log n/log (h + 1)) with high probability. Both of these bounds are asymptotically optimal for the BSP model.
- OSTI ID:
- 471735
- Report Number(s):
- CONF-970142-; CNN: Grant CCR-8300079; Grant CCR-9625289; Grant DAAH04-96-1-0013; TRN: 97:001377-0085
- Resource Relation:
- Conference: 8. annual Association for Computing Machinery (ACM)-Society for Industrial and Applied Mathematics (SIAM) symposium on discrete algorithms, New Orleans, LA (United States), 5-7 Jan 1997; Other Information: PBD: 1997; Related Information: Is Part Of Proceedings of the eighth annual ACM-SIAM symposium on discrete algorithms; PB: 798 p.
- Country of Publication:
- United States
- Language:
- English
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