DocumentCode :
450637
Title :
A Study of the Applicability of Hopfield Decision Neural Nets to VLSI CAD
Author :
Yu, Meng-Lin
Author_Institution :
AT&T Bell Laboratories, Holmdel, NJ
fYear :
1989
fDate :
25-29 June 1989
Firstpage :
412
Lastpage :
417
Abstract :
Hopfield decision neural nets have been claimed to be good for solving a class of optimization problems such as the traveling salesman´s problem. A study was undertaken to determine if these techniques were applicable to the many optimization problems that occur in VLSI circuit design and layout. Module placement was chosen as a representative problem. It was observed that the convergence process closely resembles that of greedy hill climbing algorithms. Apart from the known problems of long simulation times and hardware implementation complexity, it was noted that the quality of solution was mediocre, at best, and highly sensitive to network parameters. Various modifications were attempted, none of which significantly improved the result. It is concluded that Hopfield neural nets do not, in their present form, provide an interesting solution to this class of CAD problems.
Keywords :
Artificial neural networks; Circuit simulation; Circuit synthesis; Design optimization; Hopfield neural networks; Neural network hardware; Neural networks; Neurons; Permission; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Design Automation, 1989. 26th Conference on
ISSN :
0738-100X
Print_ISBN :
0-89791-310-8
Type :
conf
DOI :
10.1109/DAC.1989.203433
Filename :
1586417
Link To Document :
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