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Reseach Article

A Genetic Approach to Standard Cell placement using Various Genetic Operators

by Rini Mahajan, Amit Saxena, Baljit Singh Khehra
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

@article{ 10.5120/193-332,
author = { Rini Mahajan, Amit Saxena, Baljit Singh Khehra },
title = { A Genetic Approach to Standard Cell placement using Various Genetic Operators },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 9 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 85-87 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number9/193-332/ },
doi = { 10.5120/193-332 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:43:21.400694+05:30
%A Rini Mahajan
%A Amit Saxena
%A Baljit Singh Khehra
%T A Genetic Approach to Standard Cell placement using Various Genetic Operators
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 9
%P 85-87
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
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
  1. Goldberg, D.E. (1989): Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
  2. J. H. Holland Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan, 1972.
  3. 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.
  4. 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.
Index Terms

Computer Science
Information Sciences

Keywords

Population Genes chromosomes crossover mutation