Abstract
Floorplanning is an important issue in the very large-scale integrated (VLSI) circuit design automation as it determines the performance, size, yield and reliability of VLSI chips. This paper proposes a novel intelligent decision algorithm based on the particle swarm optimization (PSO) technique to obtain a feasible floorplanning in VLSI circuit physical placement. The PSO was applied with integer coding based on module number and a new recommended value of acceleration coefficients for optimal placement solution. Inspired by the physics of genetic algorithm (GA), the principles of mutation and crossover operator in GA are incorporated into the proposed PSO algorithm to make this algorithm to break away from local optima and achieve a better diversity. Experiments employing MCNC and GSRC benchmarks show that the proposed algorithm is effective. The proposed algorithm can avoid local minimum and performs well in convergence. The experimental results of the proposed method in this paper can also greatly help floorplanning decision making in VLSI circuit design automation.
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Acknowledgments
This work is supported by the National Basic Research Program of China under Grant No. 2006CB805904, the National Natural Science Foundation of China under Grant No. 10871221, the Key Project of Fujian Provincial Natural Science Foundation of China under Grant No. A0820002, Fujian Provincial Natural Science Foundation of China under Grant No. 2009J01284, the project development foundation of Education Committee of Fujian province under Grand No. JA08011.
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Chen, G., Guo, W. & Chen, Y. A PSO-based intelligent decision algorithm for VLSI floorplanning. Soft Comput 14, 1329–1337 (2010). https://doi.org/10.1007/s00500-009-0501-6
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DOI: https://doi.org/10.1007/s00500-009-0501-6