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GECCO
2005
Springer

Multiobjective VLSI cell placement using distributed genetic algorithm

10 years 19 days ago
Multiobjective VLSI cell placement using distributed genetic algorithm
Genetic Algorithms have worked fairly well for the VLSI cell placement problem, albeit with significant run times. Two parallel models for GA are presented for VLSI cell placement where the objectives are optimizing power dissipation, timing performance and interconnect wirelength, while layout width is a constraint. A Master-Slave approach is mentioned wherein both fitness calculation and crossover mechanism are distributed among slaves. A Multi-Deme parallel GA is also presented in which each processor works independently on an allocated subpopulation followed by information exchange through migration of chromosomes. A pseudo-diversity approach is taken, wherein similar solutions with the same overall cost values are not permitted in the population at any given time. A series of experiments are performed on ISCAS-85/89 benchmarks to show the performance of the Multi-Deme approach. Categories and Subject Descriptors
Sadiq M. Sait, Mohammed Faheemuddin, Mahmood R. Mi
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Sadiq M. Sait, Mohammed Faheemuddin, Mahmood R. Minhas, Syed Sanaullah
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