EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING

The problem of partitioning appears in several areas ranging from VLSI, parallel programming, to molecular biology. The interest in finding an optimal partitioning especially in VLSI, and has been a hot issue in recent years. In VLSI circuit partitioning, the problem of obtaining a minimum cut was o...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Sait, Sadiq M. (author)
مؤلفون آخرون: El-Maleh, Aiman H. (author), Al-Abaji, Raslan H. (author), unknown (author)
التنسيق: article
منشور في: 2020
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/1598/1/P131.pdf
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author Sait, Sadiq M.
author2 El-Maleh, Aiman H.
Al-Abaji, Raslan H.
unknown
author2_role author
author
author
author_facet Sait, Sadiq M.
El-Maleh, Aiman H.
Al-Abaji, Raslan H.
unknown
author_role author
dc.creator.none.fl_str_mv Sait, Sadiq M.
El-Maleh, Aiman H.
Al-Abaji, Raslan H.
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/1598/1/P131.pdf
EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING. The 6th Saudi Engineering Conference, KFUPM, Dhahran, December 2002.
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/1598/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.title.none.fl_str_mv EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description The problem of partitioning appears in several areas ranging from VLSI, parallel programming, to molecular biology. The interest in finding an optimal partitioning especially in VLSI, and has been a hot issue in recent years. In VLSI circuit partitioning, the problem of obtaining a minimum cut was of prime importance. Furthermore, with current trends partitioning has become a multi-objective problem, where power, delay and area in addition to minimum cut, need to be optimized. In this paper we employ two iterative heuristics for the optimization of VLSI Netlist Bi-Partitioning. These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) [sadiq et al., 1999] respectively. Fuzzy rules are incorporated in order to design a multiobjective cost function. Both the techniques are applied to ISCAS-85/89 benchmark circuits and experimental results are reported and compared.
eu_rights_str_mv openAccess
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identifier_str_mv EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING. The 6th Saudi Engineering Conference, KFUPM, Dhahran, December 2002.
language_invalid_str_mv en
network_acronym_str KFUPM
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spelling EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONINGSait, Sadiq M.El-Maleh, Aiman H.Al-Abaji, Raslan H.unknownThe problem of partitioning appears in several areas ranging from VLSI, parallel programming, to molecular biology. The interest in finding an optimal partitioning especially in VLSI, and has been a hot issue in recent years. In VLSI circuit partitioning, the problem of obtaining a minimum cut was of prime importance. Furthermore, with current trends partitioning has become a multi-objective problem, where power, delay and area in addition to minimum cut, need to be optimized. In this paper we employ two iterative heuristics for the optimization of VLSI Netlist Bi-Partitioning. These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) [sadiq et al., 1999] respectively. Fuzzy rules are incorporated in order to design a multiobjective cost function. Both the techniques are applied to ISCAS-85/89 benchmark circuits and experimental results are reported and compared.ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/1598/1/P131.pdf EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING. The 6th Saudi Engineering Conference, KFUPM, Dhahran, December 2002. enhttps://eprints.kfupm.edu.sa/id/eprint/1598/2020info:eu-repo/semantics/openAccessoai::15982019-11-01T13:27:27Z
spellingShingle EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
Sait, Sadiq M.
status_str publishedVersion
title EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
title_full EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
title_fullStr EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
title_full_unstemmed EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
title_short EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
title_sort EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING
url https://eprints.kfupm.edu.sa/id/eprint/1598/1/P131.pdf