Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm

In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. T...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Mathematical problems in engineering 2014, Vol.2014 (2014), p.1-15
Hauptverfasser: Shanavas, I. Hameem, Gnanamurthy, R. K.
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 15
container_issue 2014
container_start_page 1
container_title Mathematical problems in engineering
container_volume 2014
creator Shanavas, I. Hameem
Gnanamurthy, R. K.
description In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.
format Article
fullrecord <record><control><sourceid>emarefa</sourceid><recordid>TN_cdi_emarefa_primary_499854</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>499854</sourcerecordid><originalsourceid>FETCH-emarefa_primary_4998543</originalsourceid><addsrcrecordid>eNqFjd0KgjAARkcUZD-PEOwFBKdb6aX0D0GBFd3JsqmL_cg2L3z7JLrv6nxwPjgD4CGyjHyC8GrY7yDEPgqjxxhMrH0HQYgIij2QnRvHJRUw06J1XCtYagPvp-wIL3VnedGrDbO8UjBtnZb0-7lZrip46J6Gv-CeKeZ4AVNRacNdLWdgVFJh2fzHKVjsttf1wWeSGlbSvDF90nQ5TpKY4Oif_wABxD02</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm</title><source>Wiley-Blackwell Open Access Titles</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Alma/SFX Local Collection</source><creator>Shanavas, I. Hameem ; Gnanamurthy, R. K.</creator><creatorcontrib>Shanavas, I. Hameem ; Gnanamurthy, R. K.</creatorcontrib><description>In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Puplishing Corporation</publisher><ispartof>Mathematical problems in engineering, 2014, Vol.2014 (2014), p.1-15</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Shanavas, I. Hameem</creatorcontrib><creatorcontrib>Gnanamurthy, R. K.</creatorcontrib><title>Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm</title><title>Mathematical problems in engineering</title><description>In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.</description><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqFjd0KgjAARkcUZD-PEOwFBKdb6aX0D0GBFd3JsqmL_cg2L3z7JLrv6nxwPjgD4CGyjHyC8GrY7yDEPgqjxxhMrH0HQYgIij2QnRvHJRUw06J1XCtYagPvp-wIL3VnedGrDbO8UjBtnZb0-7lZrip46J6Gv-CeKeZ4AVNRacNdLWdgVFJh2fzHKVjsttf1wWeSGlbSvDF90nQ5TpKY4Oif_wABxD02</recordid><startdate>2014</startdate><enddate>2014</enddate><creator>Shanavas, I. Hameem</creator><creator>Gnanamurthy, R. K.</creator><general>Hindawi Puplishing Corporation</general><scope>ADJCN</scope><scope>AHFXO</scope></search><sort><creationdate>2014</creationdate><title>Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm</title><author>Shanavas, I. Hameem ; Gnanamurthy, R. K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-emarefa_primary_4998543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shanavas, I. Hameem</creatorcontrib><creatorcontrib>Gnanamurthy, R. K.</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><jtitle>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shanavas, I. Hameem</au><au>Gnanamurthy, R. K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2014</date><risdate>2014</risdate><volume>2014</volume><issue>2014</issue><spage>1</spage><epage>15</epage><pages>1-15</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Puplishing Corporation</pub><tpages>15</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1024-123X
ispartof Mathematical problems in engineering, 2014, Vol.2014 (2014), p.1-15
issn 1024-123X
1563-5147
language eng
recordid cdi_emarefa_primary_499854
source Wiley-Blackwell Open Access Titles; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection
title Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T11%3A07%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-emarefa&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimal%20Solution%20for%20VLSI%20Physical%20Design%20Automation%20Using%20Hybrid%20Genetic%20Algorithm&rft.jtitle=Mathematical%20problems%20in%20engineering&rft.au=Shanavas,%20I.%20Hameem&rft.date=2014&rft.volume=2014&rft.issue=2014&rft.spage=1&rft.epage=15&rft.pages=1-15&rft.issn=1024-123X&rft.eissn=1563-5147&rft_id=info:doi/&rft_dat=%3Cemarefa%3E499854%3C/emarefa%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true