Migration Effects of Parallel Genetic Algorithms on Line Topologies of Heterogeneous Computing Resources
Summary :
This paper investigates migration effects of parallel genetic algorithms (GAs) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is evaluated experimentally on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangements. Migration effects are evaluated from the viewpoints of scalability, chromosome diversity, migration frequency and solution quality. The results reveal that the performance of parallel GAs strongly depends on the design of the chromosome migration in which we need to consider the arrangement of heterogeneous computing resources, the migration frequency and so on. The results contribute to provide referential scheme of implementation of parallel GAs on heterogeneous computing resources.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.4 pp.1121-1128
- Publication Date
- 2008/04/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.4.1121
- Type of Manuscript
- Special Section PAPER (Special Section on Selected Papers from the 20th Workshop on Circuits and Systems in Karuizawa)
- Category
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Yiyuan GONG, Senlin GUAN, Morikazu NAKAMURA, "Migration Effects of Parallel Genetic Algorithms on Line Topologies of Heterogeneous Computing Resources" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 4, pp. 1121-1128, April 2008, doi: 10.1093/ietfec/e91-a.4.1121.
Abstract: This paper investigates migration effects of parallel genetic algorithms (GAs) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is evaluated experimentally on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangements. Migration effects are evaluated from the viewpoints of scalability, chromosome diversity, migration frequency and solution quality. The results reveal that the performance of parallel GAs strongly depends on the design of the chromosome migration in which we need to consider the arrangement of heterogeneous computing resources, the migration frequency and so on. The results contribute to provide referential scheme of implementation of parallel GAs on heterogeneous computing resources.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.4.1121/_p
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@ARTICLE{e91-a_4_1121,
author={Yiyuan GONG, Senlin GUAN, Morikazu NAKAMURA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Migration Effects of Parallel Genetic Algorithms on Line Topologies of Heterogeneous Computing Resources},
year={2008},
volume={E91-A},
number={4},
pages={1121-1128},
abstract={This paper investigates migration effects of parallel genetic algorithms (GAs) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is evaluated experimentally on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangements. Migration effects are evaluated from the viewpoints of scalability, chromosome diversity, migration frequency and solution quality. The results reveal that the performance of parallel GAs strongly depends on the design of the chromosome migration in which we need to consider the arrangement of heterogeneous computing resources, the migration frequency and so on. The results contribute to provide referential scheme of implementation of parallel GAs on heterogeneous computing resources.},
keywords={},
doi={10.1093/ietfec/e91-a.4.1121},
ISSN={1745-1337},
month={April},}
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TY - JOUR
TI - Migration Effects of Parallel Genetic Algorithms on Line Topologies of Heterogeneous Computing Resources
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1121
EP - 1128
AU - Yiyuan GONG
AU - Senlin GUAN
AU - Morikazu NAKAMURA
PY - 2008
DO - 10.1093/ietfec/e91-a.4.1121
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2008
AB - This paper investigates migration effects of parallel genetic algorithms (GAs) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is evaluated experimentally on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangements. Migration effects are evaluated from the viewpoints of scalability, chromosome diversity, migration frequency and solution quality. The results reveal that the performance of parallel GAs strongly depends on the design of the chromosome migration in which we need to consider the arrangement of heterogeneous computing resources, the migration frequency and so on. The results contribute to provide referential scheme of implementation of parallel GAs on heterogeneous computing resources.
ER -
English
