Title :
The role of learning in logic synthesis
Author :
Kipps, James R. ; Gajski, Daniel D.
Author_Institution :
Dept. of Inf. & Comput. Sci., California Univ., Irvine, CA, USA
Abstract :
A model of logic synthesis that uses technology-specific design rules and extends rule-based search to functional decomposition and technology mapping is proposed. The problem of technology independence is addressed with the addition of a model of learning for automating the generation of design rules. While this model improves design quality by taking advantage of the target technology, it is not robust to technology changes. To improve robustness, the model is augmented with two learning components: one for acquiring rules that make use of physical cells in a technology library and another for acquiring rules that make use of appropriate design styles. These components are related to work in the learning of macro-operators and explanation-based learning
Keywords :
explanation; integrated logic circuits; knowledge acquisition; knowledge based systems; learning systems; logic CAD; acquiring rules; design quality; explanation-based learning; functional decomposition; learning; logic synthesis; macro-operators; physical cells; robustness; rule-based search; technology independence; technology library; technology mapping; technology-specific design rules; Appropriate technology; Computer science; Constraint optimization; Design optimization; Hardware; Large scale integration; Libraries; Logic design; Machine learning; Robustness;
Conference_Titel :
Tools for Artificial Intelligence, 1989. Architectures, Languages and Algorithms, IEEE International Workshop on
Conference_Location :
Fairfax, VA
Print_ISBN :
0-8186-1984-8
DOI :
10.1109/TAI.1989.65328