Title :
Neural networks as massively parallel automatic test pattern generators
Author :
Majumder, A. ; Dandapani, R.
Author_Institution :
Motorola Inc., Austin, TX, USA
Abstract :
Neural networks are characterized by small-grain parallelism where a large number of inexpensive neurons (processors) can act simultaneously toward solving a given optimization problem. Neural networks present a promising paradigm for computationally intensive CAD applications like automatic test pattern generation (ATPG) for digital circuits. The performances of 2-Valued and 3-Valued neural networks as ATPGs are compared. The performance data are obtained by implementing the neural network-based ATPGs on the Myrias Scalable Parallel Supercomputer
Keywords :
automatic testing; integrated circuit testing; logic testing; neural nets; parallel processing; ATPGs; Myrias Scalable Parallel Supercomputer; automatic test pattern generators; computationally intensive CAD; massively parallel; neural networks; small-grain parallelism; three-valued networks; two-valued networks; Automatic test pattern generation; Automatic testing; Circuit testing; Computer applications; Computer networks; Digital circuits; Neural networks; Neurons; Parallel processing; Supercomputers;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298817
