Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations

Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinatorial optimization problems. However, depending on the size of the problem, it may have large run-time requirements. One practical approach to speed up its execution is to parallelize it. In this paper,...

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Main Author: Sait, Sadiq M. (author)
Other Authors: Zaidi, Ali Mustafa (author), Ali, Mustafa I. (author), unknown (author)
Format: article
Published: 2020
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Online Access:https://eprints.kfupm.edu.sa/id/eprint/252/1/J_Sait_JCC_September2007.pdf
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author Sait, Sadiq M.
author2 Zaidi, Ali Mustafa
Ali, Mustafa I.
unknown
author2_role author
author
author
author_facet Sait, Sadiq M.
Zaidi, Ali Mustafa
Ali, Mustafa I.
unknown
author_role author
dc.creator.none.fl_str_mv Sait, Sadiq M.
Zaidi, Ali Mustafa
Ali, Mustafa I.
unknown
dc.date.*.fl_str_mv 2020
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/252/1/J_Sait_JCC_September2007.pdf
Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations. Journal of CLUSTER COMPUTING: SUBMITTED: SEPT 2007.
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/252/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Simulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinatorial optimization problems. However, depending on the size of the problem, it may have large run-time requirements. One practical approach to speed up its execution is to parallelize it. In this paper, several parallel SA schemes based on the Asynchronous Multiple-Markov Chain model are explored. We investigate the speedup and solution quality characteristics of each scheme when implemented on an inexpensive cluster of workstations for solving a multi-objective cell placement problem. This problem requires the optimization of conicting objectives (interconnect wire-length, power dissipation, and timing performance), and Fuzzy logic is used to integrate the costs of these objectives. Our goal is to develop several AMMC based parallel SA schemes and explore their suitability for different objectives: achieving near linear speedups while still meeting solution quality targets, and obtaining higher quality solutions in the least possible duration.
eu_rights_str_mv openAccess
format article
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identifier_str_mv Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations. Journal of CLUSTER COMPUTING: SUBMITTED: SEPT 2007.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::252
publishDate 2020
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spelling Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-WorkstationsSait, Sadiq M.Zaidi, Ali MustafaAli, Mustafa I.unknownComputerSimulated Annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinatorial optimization problems. However, depending on the size of the problem, it may have large run-time requirements. One practical approach to speed up its execution is to parallelize it. In this paper, several parallel SA schemes based on the Asynchronous Multiple-Markov Chain model are explored. We investigate the speedup and solution quality characteristics of each scheme when implemented on an inexpensive cluster of workstations for solving a multi-objective cell placement problem. This problem requires the optimization of conicting objectives (interconnect wire-length, power dissipation, and timing performance), and Fuzzy logic is used to integrate the costs of these objectives. Our goal is to develop several AMMC based parallel SA schemes and explore their suitability for different objectives: achieving near linear speedups while still meeting solution quality targets, and obtaining higher quality solutions in the least possible duration.ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/252/1/J_Sait_JCC_September2007.pdf Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations. Journal of CLUSTER COMPUTING: SUBMITTED: SEPT 2007. enhttps://eprints.kfupm.edu.sa/id/eprint/252/2020info:eu-repo/semantics/openAccessoai::2522019-11-01T13:23:13Z
spellingShingle Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
Sait, Sadiq M.
Computer
status_str publishedVersion
title Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
title_full Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
title_fullStr Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
title_full_unstemmed Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
title_short Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
title_sort Exploring Asynchronous MMC based Parallel SA Schemes for Multiobjective Cell Placement on a Cluster-of-Workstations
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/252/1/J_Sait_JCC_September2007.pdf