IEICE TRANSACTIONS on Fundamentals
Designing Efficient Parallel Algorithms with Multi-Level Divide-and-Conquer
Summary :
Multi-level divide-and-conquer (MDC) is a generalized divide-and-conquer technique, which consists of more than one division step organized hierarchically. In this paper, we investigate the paradigm of the MDC and show that it is an efficient technique for designing parallel algorithms. The following parallel algorithms are used for studying the MDC: finding the convex hull of discs, finding the upper envelope of line segments, finding the farthest neighbors of a convex polygon and finding all the row maxima of a totally monotone matrix. The third and the fourth algorithms are newly presented. Our discussion is based on the EREW PRAM, but the methods discussed here can be applied to any parallel computation models.
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- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.5 pp.1201-1208
- Publication Date
- 2001/05/01
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- Special Section PAPER (Special Section on Discrete Mathematics and Its Applications)
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Wei CHEN, Koichi WADA, "Designing Efficient Parallel Algorithms with Multi-Level Divide-and-Conquer" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 5, pp. 1201-1208, May 2001, doi: .
Abstract: Multi-level divide-and-conquer (MDC) is a generalized divide-and-conquer technique, which consists of more than one division step organized hierarchically. In this paper, we investigate the paradigm of the MDC and show that it is an efficient technique for designing parallel algorithms. The following parallel algorithms are used for studying the MDC: finding the convex hull of discs, finding the upper envelope of line segments, finding the farthest neighbors of a convex polygon and finding all the row maxima of a totally monotone matrix. The third and the fourth algorithms are newly presented. Our discussion is based on the EREW PRAM, but the methods discussed here can be applied to any parallel computation models.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_5_1201/_p
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@ARTICLE{e84-a_5_1201,
author={Wei CHEN, Koichi WADA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Designing Efficient Parallel Algorithms with Multi-Level Divide-and-Conquer},
year={2001},
volume={E84-A},
number={5},
pages={1201-1208},
abstract={Multi-level divide-and-conquer (MDC) is a generalized divide-and-conquer technique, which consists of more than one division step organized hierarchically. In this paper, we investigate the paradigm of the MDC and show that it is an efficient technique for designing parallel algorithms. The following parallel algorithms are used for studying the MDC: finding the convex hull of discs, finding the upper envelope of line segments, finding the farthest neighbors of a convex polygon and finding all the row maxima of a totally monotone matrix. The third and the fourth algorithms are newly presented. Our discussion is based on the EREW PRAM, but the methods discussed here can be applied to any parallel computation models.},
keywords={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - Designing Efficient Parallel Algorithms with Multi-Level Divide-and-Conquer
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1201
EP - 1208
AU - Wei CHEN
AU - Koichi WADA
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2001
AB - Multi-level divide-and-conquer (MDC) is a generalized divide-and-conquer technique, which consists of more than one division step organized hierarchically. In this paper, we investigate the paradigm of the MDC and show that it is an efficient technique for designing parallel algorithms. The following parallel algorithms are used for studying the MDC: finding the convex hull of discs, finding the upper envelope of line segments, finding the farthest neighbors of a convex polygon and finding all the row maxima of a totally monotone matrix. The third and the fourth algorithms are newly presented. Our discussion is based on the EREW PRAM, but the methods discussed here can be applied to any parallel computation models.
ER -
English
