Detail publikace

On Area Minimization of Complex Combinational Circuits Using Cartesian Genetic Programming

VAŠÍČEK, Z. SEKANINA, L.

Originální název

On Area Minimization of Complex Combinational Circuits Using Cartesian Genetic Programming

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The paper deals with the evolutionary post synthesis optimization of complex combinational circuits with the aim of reducing the area on a chip as much as possible. In order to optimize complex circuits, Cartesian Genetic Programming (CGP) is employed where the fitness function is based on a formal equivalence checking algorithm rather than evaluating all possible input assignments. The standard selection strategy of CGP is modified to be more explorative and so agile in very rugged fitness landscapes. It was shown on the LGSynth93 benchmark circuits that the modified selection strategy leads to more compact circuits in roughly 50% cases. The average area improvement is 24% with respect to the results of conventional synthesis. Delay of optimized circuits was also analyzed. 

Klíčová slova

logic synthesis, optimization, genetic programming, selection

Autoři

VAŠÍČEK, Z.; SEKANINA, L.

Rok RIV

2012

Vydáno

10. 6. 2012

Nakladatel

Institute of Electrical and Electronics Engineers

Místo

CA

ISBN

978-1-4673-1508-1

Kniha

2012 IEEE World Congress on Computational Intelligence

Strany od

2379

Strany do

2386

Strany počet

6

URL

https://www.fit.vut.cz/research/publication/9866/

BibTex

@inproceedings{BUT96926,
  author="Zdeněk {Vašíček} and Lukáš {Sekanina}",
  title="On Area Minimization of Complex Combinational Circuits Using Cartesian Genetic Programming",
  booktitle="2012 IEEE World Congress on Computational Intelligence",
  year="2012",
  pages="2379--2386",
  publisher="Institute of Electrical and Electronics Engineers",
  address="CA",
  doi="10.1109/CEC.2012.6256649",
  isbn="978-1-4673-1508-1",
  url="https://www.fit.vut.cz/research/publication/9866/"
}

Dokumenty

cec_ls.pdf