SNAP: Parallel Processing Applied to AI

Authors:
Dan Moldovan;Wing Lee;Changhwa Lin;Minhwa Chung
Affiliations:
Univ. of Southern California, Los Angeles;Univ. of Southern California, Los Angeles;Univ. of Southern California, Los Angeles;Univ. of Southern California, Los Angeles
Venue:
Computer
Year:
1992

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Abstract

It is argued that a viable solution for building future intelligent systems is to design special-purpose parallel computer architectures. The applications are restricted to those using semantic networks for knowledge representation. Reasoning on these networks is achieved with a marker-passing model of processing. The Semantic Network Array Processor (SNAP), a marker-passing parallel computer dedicated for natural-language and other knowledge-processing applications, is considered. Solutions for several nontrivial natural-language problems using the marker-passing approach are discussed.