A parallel genetic algorithm for floorplan area optimization

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

14 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationProceedings of The 7th International Conference on Intelligent Systems Design and Applications, ISDA 2007
Pages801-806
Publication statusPublished - 2007

Conference

Title7th International Conference on Intelligent Systems Design and Applications, ISDA'07
PlaceBrazil
CityRio de Janeiro
Period22 - 24 October 2007

Abstract

Floorplanning is an important problem in Very Large-Scale Integrated-circuit (VLSI) design automation as it determines the performance, size, yield and reliability of VLSI chips. From the computational point of view. floorplan area minimization is an NP-hard problem. This paper presents a parallel genetic algorithm (GA) for floorplan area optimization. The parallel GA is based an island model with an asynchronous migration mechanism, and is implemented using Web services and multithreading technologies. The parallel GA is compared with a sequential GA that the parallel GA is based on. Experimental results show that the parallel GA can produce better results than the sequential GA when they use the same amount of computing resources. In addition, since the number of islands and migration interval are two important parameters that directly affect the performance of island-based parallel GAs, the impact of the two parameters on the performance of the parallel GA are empirically studied in this paper. © 2007 IEEE.

Citation Format(s)

A parallel genetic algorithm for floorplan area optimization. / Tang, Maolin; Lau, Raymond Y.K.
Proceedings of The 7th International Conference on Intelligent Systems Design and Applications, ISDA 2007. 2007. p. 801-806 4389706.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review