Title :
K-selection in hypercubes
Author_Institution :
Lab. de l´´Inf. du Parallelisme, Ecole Normale Superieure de Lyon, France
Abstract :
This paper deals with the problem of finding the K smallest elements out of a totally ordered but non sorted set of N elements. This problem, called K-selection, arises often in statistics, image processing and distributed computing. The author´s algorithm has a worst-case complexity O(log K(log log K)2+log K log log N/K+log N/K) on a hypercube of size N, which is asymptotically optimal when K=(log N)β, for any constant β. This is a great improvement on previous results. The author addresses the universal K-selection problem as well
Keywords :
computational complexity; hypercube networks; parallel algorithms; K-selection; hypercubes; worst-case complexity; Distributed computing; Hypercubes; Image processing; Merging; Parallel algorithms; Sorting; Statistical distributions; Upper bound;
Conference_Titel :
Computing and Information, 1992. Proceedings. ICCI '92., Fourth International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-8186-2812-X
DOI :
10.1109/ICCI.1992.227681