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FPGA placement using genetic algorithm with simulated annealing.

Yang, M, Almaini, A E A, Wang, Lun Yao and Wang, P (2005) FPGA placement using genetic algorithm with simulated annealing. ASICON 2005: Proceedings of the 6th International Conference on ASIC, 2005, 2. pp. 808-811. ISSN 0 7803 9210 8

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Abstract/Description

A mixed Genetic Algorithm and Simulated Annealing (GASA) algorithm is used for the placement of symmetrical FPGA. The prpoposed algortithm includes 2 stage processes. In the first stage process it optimizes placement solutions globally using GA. In the second stage process it locally improves solution. GASA overcomes the slow convergence in the later phases of processing by a genetic algorithm. The results show that GASA consumes less CPU time than GA and could achieve performances as good as versatile placement and routing tools in terms of placement cost.

Item Type: Article
Print ISSN: 0 7803 9210 8
Additional Information: “© © 2005 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
Uncontrolled Keywords: Genetic algorithms; Deveopments; Simulated annealing; Computer programming; CPU time; Routing tools; Placement costs;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 006 Special Computer Methods > 006.3 Artificial intelligence
600 Technology > 620 Engineering > 621 Electronic & mechanical engineering > 621.3 Electrical & electronic engineering > 621.38 Electronics & Communications engineering > 621.389 Computer engineering
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science > 004.2 Systems analysis, design & performance
Library of Congress Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 2570
Depositing User: Dr. David A. Cumming
Date Deposited: 08 May 2009 11:49
Last Modified: 03 Apr 2013 14:44
URI: http://researchrepository.napier.ac.uk/id/eprint/2570

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