A neural network for scheduling and allocation in VLSI design

Author

Wu, Xing-Qiang ; Carothers, Jo Dale ; Gassen, David

Author_Institution

Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA

Volume

3

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

1939

Abstract

Neural networks have shown success in solving some difficult optimization problems. Problems become more complex, it is increasingly difficult to find a suitable encoding of constraints into an energy function, which will effectively guide the network to a desired solution. In previous work by Gassen and Carothers (1993), a difficult scheduling problem in VLSI design was encoded into a Hopfield-type neural network. In this paper, we report significant enhancements which allow additional design constraints to be considered and more flexibility for considering the specific design under development

Keywords

Hopfield neural nets; VLSI; circuit CAD; integrated circuit design; optimisation; scheduling; Hopfield-type neural network; VLSI design; allocation; energy function; scheduling; Clocks; Design optimization; Encoding; Hopfield neural networks; Intelligent networks; Network synthesis; Neural networks; Neurons; Processor scheduling; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374457

Filename

374457