Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning

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

Full description

Saved in:
Bibliographic Details
Main Author: Sait, Sadiq M. (author)
Other Authors: El-Maleh, Aiman H. (author), Al-Abaji, RH (author), unknown (author)
Format: article
Published: 2006
Subjects:
Online Access:https://eprints.kfupm.edu.sa/id/eprint/259/1/J_Sait_EAAI_April2006.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864513388486328320
author Sait, Sadiq M.
author2 El-Maleh, Aiman H.
Al-Abaji, RH
unknown
author2_role author
author
author
author_facet Sait, Sadiq M.
El-Maleh, Aiman H.
Al-Abaji, RH
unknown
author_role author
dc.creator.none.fl_str_mv Sait, Sadiq M.
El-Maleh, Aiman H.
Al-Abaji, RH
unknown
dc.date.none.fl_str_mv 2006-04
2020
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/259/1/J_Sait_EAAI_April2006.pdf
(2006) Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning. ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS 13 (1): 15-21 MAR 2005.
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/259/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Abstract. The problem of partitioning appears in several areas ranging from VLSI, parallel programming, to molecular biology. The interest in finding an optimal partition especially in VLSI has been a hot issue in recent years. In VLSI circuit partitioning, the problem of obtaining a minimum cut is of prime importance. With current trends, partitioning with multiple objectives which includes power, delay and area, in addition to minimum cut is in vogue. In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-Partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). Fuzzy rules are incorporated in order to handle the multiobjective cost function. For SimE, fuzzy goodness functions are designed for delay and power, and proved efficient. A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. PowerFM performs better in terms of power dissipation for smaller circuits. For larger sized circuits SimE outperforms PowerFM in terms of all three, delay, number of net cuts, and power dissipation. Keywords: Genetic Algorithms, Tabu Search, Simulated Evolution, multiobjective, Fuzzy Logic, Netlist partitioning.
eu_rights_str_mv openAccess
format article
id KFUPM_26713be5cffeb3481999492d9bed7ff4
identifier_str_mv (2006) Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning. ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS 13 (1): 15-21 MAR 2005.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::259
publishDate 2006
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Evolutionary Algorithms for VLSIMultiobjective Netlist PartitioningSait, Sadiq M.El-Maleh, Aiman H.Al-Abaji, RHunknownComputerAbstract. The problem of partitioning appears in several areas ranging from VLSI, parallel programming, to molecular biology. The interest in finding an optimal partition especially in VLSI has been a hot issue in recent years. In VLSI circuit partitioning, the problem of obtaining a minimum cut is of prime importance. With current trends, partitioning with multiple objectives which includes power, delay and area, in addition to minimum cut is in vogue. In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-Partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). Fuzzy rules are incorporated in order to handle the multiobjective cost function. For SimE, fuzzy goodness functions are designed for delay and power, and proved efficient. A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. PowerFM performs better in terms of power dissipation for smaller circuits. For larger sized circuits SimE outperforms PowerFM in terms of all three, delay, number of net cuts, and power dissipation. Keywords: Genetic Algorithms, Tabu Search, Simulated Evolution, multiobjective, Fuzzy Logic, Netlist partitioning.2006-042020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/259/1/J_Sait_EAAI_April2006.pdf (2006) Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning. ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS 13 (1): 15-21 MAR 2005. enhttps://eprints.kfupm.edu.sa/id/eprint/259/info:eu-repo/semantics/openAccessoai::2592019-11-01T13:23:15Z
spellingShingle Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
Sait, Sadiq M.
Computer
status_str publishedVersion
title Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
title_full Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
title_fullStr Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
title_full_unstemmed Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
title_short Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
title_sort Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/259/1/J_Sait_EAAI_April2006.pdf