Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement

Simulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to well established stochastic heuristics such as SA, TS and GA, with shorter runtimes. However, for optimization problems with a very large set of elements, such as in VLSI cell placement and routing, r...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Sait, Sadiq M. (author)
مؤلفون آخرون: Ali, Mustafa I. (author), Zaidi, Ali Mustafa (author), unknown (author)
التنسيق: article
منشور في: 2007
الموضوعات:
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/229/1/sait_jmma.pdf
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author Sait, Sadiq M.
author2 Ali, Mustafa I.
Zaidi, Ali Mustafa
unknown
author2_role author
author
author
author_facet Sait, Sadiq M.
Ali, Mustafa I.
Zaidi, Ali Mustafa
unknown
author_role author
dc.creator.none.fl_str_mv Sait, Sadiq M.
Ali, Mustafa I.
Zaidi, Ali Mustafa
unknown
dc.date.none.fl_str_mv 2007-09
2020
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/229/1/sait_jmma.pdf
(2007) Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement. Journal of Mathematical Modelling and Algorithms (JMMA), 6 (3). pp. 433-454. ISSN 1570-1166 (Print) 1572-9214 (Online)
10.1007/s10852-007-9064-7
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Springer Netherlands
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/229/
http://www.springerlink.com/content/108992/
10.1007/s10852-007-9064-7
dc.rights.none.fl_str_mv cc_by_nc_nd
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Simulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to well established stochastic heuristics such as SA, TS and GA, with shorter runtimes. However, for optimization problems with a very large set of elements, such as in VLSI cell placement and routing, runtimes can still be very large and parallelization is an attractive option for reducing runtimes. Compared to other metaheuristics, parallelization of SimE has not been extensively explored. This paper presents a comprehensive set of parallelization approaches for SimE when applied to multiobjective VLSI cell placement problem. Each of these approaches are evaluated with respect to SimE characteristics and the constraints imposed by the problem instance. Conclusions drawn can be extended to parallelization of SimE when applied to other optimization problems.
eu_rights_str_mv openAccess
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id KFUPM_c81def46dce004662ed1882a5fc8a5f5
identifier_str_mv (2007) Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement. Journal of Mathematical Modelling and Algorithms (JMMA), 6 (3). pp. 433-454. ISSN 1570-1166 (Print) 1572-9214 (Online)
10.1007/s10852-007-9064-7
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::229
publishDate 2007
publisher.none.fl_str_mv Springer Netherlands
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spelling Evaluating Parallel Simulated Evolution Strategies for VLSI Cell PlacementSait, Sadiq M.Ali, Mustafa I.Zaidi, Ali MustafaunknownComputerSimulated Evolution (SimE) is an evolutionary metaheuristic that has produced results comparable to well established stochastic heuristics such as SA, TS and GA, with shorter runtimes. However, for optimization problems with a very large set of elements, such as in VLSI cell placement and routing, runtimes can still be very large and parallelization is an attractive option for reducing runtimes. Compared to other metaheuristics, parallelization of SimE has not been extensively explored. This paper presents a comprehensive set of parallelization approaches for SimE when applied to multiobjective VLSI cell placement problem. Each of these approaches are evaluated with respect to SimE characteristics and the constraints imposed by the problem instance. Conclusions drawn can be extended to parallelization of SimE when applied to other optimization problems.Springer Netherlands2007-092020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/229/1/sait_jmma.pdf (2007) Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement. Journal of Mathematical Modelling and Algorithms (JMMA), 6 (3). pp. 433-454. ISSN 1570-1166 (Print) 1572-9214 (Online) 10.1007/s10852-007-9064-7enhttps://eprints.kfupm.edu.sa/id/eprint/229/http://www.springerlink.com/content/108992/10.1007/s10852-007-9064-7cc_by_nc_ndinfo:eu-repo/semantics/openAccessoai::2292020-12-31T08:29:48Z
spellingShingle Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
Sait, Sadiq M.
Computer
status_str publishedVersion
title Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
title_full Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
title_fullStr Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
title_full_unstemmed Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
title_short Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
title_sort Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/229/1/sait_jmma.pdf