Persistent Link:
http://hdl.handle.net/10150/291564
Title:
A performance-driven fuzzy algorithm for placement of macro cells
Author:
Mackey, Carol Ann
Issue Date:
1995
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Macro cell placement is an integral part of VLSI design. Existing placement techniques do not use a realistic human-like intuitive process for making decisions and therefore, lack the ability to make decisions based on several factors at once. In this research a quad-partitioning algorithm with a tabu search and a fuzzy cost function is used for macro cell placement. This approach partitions the design into small pieces that can be easily placed. The algorithm is based on a method which tries to reduce the path lengths and reduce the number of edges which cross out of a partition. The fuzzy cost function adds the human reasoning missing from other algorithms. The algorithm allows I/O cells to be preplaced or it can optimize their placement. The results show that this algorithm produces higher quality placements than other macro cell algorithms such as Lim, Chee and Wu and Lin and Du.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Engineering, Electronics and Electrical.; Artificial Intelligence.; Computer Science.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Electrical and Computer Engineering
Degree Grantor:
University of Arizona
Advisor:
Carothers, Jo Dale

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleA performance-driven fuzzy algorithm for placement of macro cellsen_US
dc.creatorMackey, Carol Annen_US
dc.contributor.authorMackey, Carol Annen_US
dc.date.issued1995en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractMacro cell placement is an integral part of VLSI design. Existing placement techniques do not use a realistic human-like intuitive process for making decisions and therefore, lack the ability to make decisions based on several factors at once. In this research a quad-partitioning algorithm with a tabu search and a fuzzy cost function is used for macro cell placement. This approach partitions the design into small pieces that can be easily placed. The algorithm is based on a method which tries to reduce the path lengths and reduce the number of edges which cross out of a partition. The fuzzy cost function adds the human reasoning missing from other algorithms. The algorithm allows I/O cells to be preplaced or it can optimize their placement. The results show that this algorithm produces higher quality placements than other macro cell algorithms such as Lim, Chee and Wu and Lin and Du.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectArtificial Intelligence.en_US
dc.subjectComputer Science.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorCarothers, Jo Daleen_US
dc.identifier.proquest1362220en_US
dc.identifier.bibrecord.b333109939en_US
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