Title :
Modular artificial neural network models for simulation and optimization of VLSI circuits
Author_Institution :
Dept. of Electr. Eng., Hartford Univ., West Hartford, CT, USA
Abstract :
A method is proposed which generates a modular neural network MANN for mapping process level parameters to circuit performance. The MANN-an adaptive mixture of local experts competing to learn different aspects of a problem-is employed in performing extremely efficient optimization of the circuit yield at minimal cost. The MANN calculates circuit performance and optimizes yield with 97% accuracy at 28% of the cost of a full SPICE simulation
Keywords :
VLSI; circuit analysis computing; circuit optimisation; digital simulation; neural nets; MANN; VLSI circuits; circuit performance; modular artificial neural network models; modular neural network; optimization; process level parameters; Artificial neural networks; Circuit optimization; Circuit simulation; Cost function; Fabrication; Manufacturing; Multi-layer neural network; Probability; SPICE; Very large scale integration;
Conference_Titel :
Simulation Symposium, 1997. Proceedings., 30th Annual
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-7934-4
DOI :
10.1109/SIMSYM.1997.586552
