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A Genetic Approach to Standard Cell placement using Various Genetic Operators
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 9 |
| Year of Publication: 2010 |
| Authors: Rini Mahajan, Amit Saxena, Baljit Singh Khehra |
10.5120/193-332
|
Rini Mahajan, Amit Saxena, Baljit Singh Khehra . A Genetic Approach to Standard Cell placement using Various Genetic Operators. International Journal of Computer Applications. 1, 9 ( February 2010), 85-87. DOI=10.5120/193-332
Abstract
Genetic algorithm (GA) is a powerful optimization algorithm, which starts with an initial set of random configurations and uses a process similar to biological evolution to improve upon them [1]. As we know that there is a progression towards miniaturization. This paper describes the Genetic Algorithm for standard cell placement on a VLSI Chip for minimization of chip area. Unlike the other placement algorithms that apply transformations on the physical layout, the genetic algorithm applies transformations on the chromosomal representation of the physical layout.
References
- Goldberg, D.E. (1989): Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
- J. H. Holland Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan, 1972.
- Shahookar, K.; Mazumder, P." A genetic approach to standard cell placement using meta-genetic parameter optimization" in Proc. IEEE Int. Conf. on Computer-Aided Design of Integrated Circuits and Systems pp. 500 - 511 , 1990.
- Youssef, H.; Sait, S.M.; Nassar, K.; Benten, M.S.T." Performance driven standard-cell placement using the genetic algorithm" Fifth Great Lakes Symposium on VLSI pp. 124 - 127, 1995.
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