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An efficient parallel algorithm for the maximum convex sum problem

Published: 01 February 2016 Publication History

Abstract

In this paper, we present a parallel algorithm for the maximum convex sum (MCS) problem, which is a generalization of the maximum subarray (MSA) problem. In the MSA problem, we find a rectangular portion within the given data array that maximizes the sum in it. The MCS problem is to find a convex shape instead of a rectangular shape that maximizes the sum. For the MSA problem, O(n) time parallel algorithms are already known on an (n, n) 2D array of processors. For the MCS problem, we achieve the same time bound of O(n) on an (n, n) 2D array of processors. We provide rigorous proofs for the correctness of our parallel algorithm based on Hoare logic and also provide some experimental results of our algorithm that are gathered from the Blue Gene/P super computer.

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ACSW '16: Proceedings of the Australasian Computer Science Week Multiconference
February 2016
654 pages
ISBN:9781450340427
DOI:10.1145/2843043
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 February 2016

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ACSW '16
ACSW '16: Australasian Computer Science Week
February 1 - 5, 2016
Canberra, Australia

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ACSW '16 Paper Acceptance Rate 77 of 172 submissions, 45%;
Overall Acceptance Rate 204 of 424 submissions, 48%

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