Parallel algorithms for all maximal equally-spaced collinear sets and all maximal regular lattices

Author

Boxer, Laurence ; Miller, Russ

Author_Institution

Dept. of Comput. & Inf. Sci., Niagara Univ., NY, USA

fYear

1992

fDate

19-21 Oct 1992

Firstpage

54

Lastpage

58

Abstract

The authors present parallel solutions to the AMESCS (all maximal equally-spaced collinear subset) and AMRSS (all maximal regularly-spaced subset) problems and show how their solutions to the latter generalize to the AMRSDLS (all maximal regularly-spaced D-dimensional lattice subsets) problem. Their algorithms differ significantly from the optimal sequential algorithms presented in A.B. Kahng and G. Robins (1991), which do not scale well to (massively) parallel machines. The optimality of the authors´ Arbitrary CRCW PRAM (parallel random access machine) algorithms is open; however, the algorithms they present are within a logarithmic factor of optimal. Further, the algorithms are optimal for the mesh-connected computer

Keywords

computational complexity; parallel algorithms; random-access storage; AMESCS; CRCW PRAM; all maximal equally-spaced collinear sets; all maximal regular lattices; all maximal regularly-spaced D-dimensional lattice subsets; mesh-connected computer; optimal sequential algorithms; parallel algorithms; parallel random access machine; Computational modeling; Computer science; Concurrent computing; Infrared surveillance; Landmine detection; Lattices; Parallel algorithms; Parallel machines; Phase change random access memory; Read-write memory;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers of Massively Parallel Computation, 1992., Fourth Symposium on the

Conference_Location

McLean, VA

Print_ISBN

0-8186-2772-7

Type

conf

DOI

10.1109/FMPC.1992.234905

Filename

234905