(2001) Iterative heuristics for multiobjective VLSI standard cellplacement. Neural Networks, 2001. Proceedings. IJCNN '01. International Joint conference, 3.

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Abstract

We employ two iterative heuristics for the optimization of VLSI standard cell placement. These heuristics are based on genetic algorithms (GA) and tabu search (TS) respectively. We address a multiobjective version of the problem, in which power dissipation, timing performance, and interconnect wire length are optimized while layout width is taken as a constraint. Fuzzy rules are incorporated in order to design a multiobjective cost function that integrates the costs of three objectives in a single overall cost value. A series of experiments is performed to study the effect of important algorithmic parameters of GA and TS. Both the techniques are applied to ISCAS-85/89 benchmark circuits and experimental results are reported and compared

Item Type:	Article
Subjects:	Computer
Department:	College of Computing and Mathematics > Computer Engineering
Depositing User:	Mr. Admin Admin
Date Deposited:	24 Jun 2008 13:40
Last Modified:	01 Nov 2019 14:06
URI:	http://eprints.kfupm.edu.sa/id/eprint/14554