## Abstract

Weighted multiselection requires to select r elements from a given set of n elements, each associated with a weight, such that, each element selected is on a pre-specified weighted-rank, where an element is on weighted-rank k if it is the smallest element such that the aggregated weight of all elements not greater than it in the set is not smaller than k. This paper presents efficient algorithms for solving this problem both sequentially and in parallel on BREW PRAM. Our sequential algorithm solves this problem in time O(n log r) which is optimal. Our parallel algorithm runs in O(T_{1} log r) time on an EREW PRAM with 1< p ≤ n processors, and is optimal with respect to T_{1} which is the time complexity for single-element weighted selection using p processors. We give a parallel algorithm for single-element weighted selection using p EREW processors which runs cost-optimally in O(n/p) time for 1 < p ≤ n log log n/ log n. and time-optimally in O(log n/ log log n) time for n log log n/ log n < p ≤ n.

Original language | English |
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Pages | 323-326 |

Number of pages | 4 |

Publication status | Published - 2002 |

Externally published | Yes |

Event | 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering - Beijing, China Duration: 28 Oct 2002 → 31 Oct 2002 |

### Conference

Conference | 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering |
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Country/Territory | China |

City | Beijing |

Period | 28/10/02 → 31/10/02 |

## Keywords

- EREW PRAM
- Multiselection
- Parallel algorithm
- Selection
- Sorting
- Weight selection