Modeling Semantic Networks on the Connection Machine

✍ Scribed by S.H. Chung; D.I. Moldovan

• Publisher: Elsevier Science
• Year: 1993
• Tongue: English
• Weight: 1007 KB
• Volume: 17
• Category: Article
• ISSN: 0743-7315
• DOI: 10.1006/jpdc.1993.1014

✦ Synopsis

Massively parallel architectures such as the Connection Machine can process large knowledge bases efficiently. An appropriate knowledge representation scheme for parallel processing is a semantic network. We have defined and implemented software data structures, marker propagation rules, and an instruction set for semantic network processing on the Connection Machine. Several experiments were performed in order to analyze the performance of our inferencing system. From these experiments, we have observed that the execution time is a linear function of the length of the critical path, rather than being proportional to the knowledge base size ( (S) ). Identical examples were executed on a SUN uniprocessor. Although the uniprocessor SUN outperforms the Connection Machine for small knowledge bases, the advantage of the parallel machine increases with the size of the problem to achieve a speed-up of (S / \log (S)) in the best case. 1993 Academic Press, Inc.