DocumentCode
2445453
Title
A Hopfield neural network solution to the TCM partitioning problem
Author
Hameenanttila, Tom ; Carothers, Jo Dale
Author_Institution
Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA
Volume
7
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
4676
Abstract
In this paper, the problem of circuit partitioning for multichip module packaging realization is considered. A Hopfield-type neural network is designed for use in solving the previously proposed thermal conduction module (TCM) partitioning problem, to which only heuristic solutions have been applied thus far. It is expected that the global nature of the Hopfield neural network´s operation will make it a useful tool as the problem complexity is increased
Keywords
Hopfield neural nets; circuit layout CAD; circuit optimisation; constraint theory; integrated circuit packaging; logic partitioning; multichip modules; Hopfield neural network; heuristic solutions; multichip module; optimisation; packaging; printed circuit board; thermal conduction module partitioning; Delay; Digital systems; Hopfield neural networks; Multichip modules; Neural networks; Packaging; Printed circuits; Routing; Silicon; Thermal conductivity;
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.1994.375031
Filename
375031
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