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DYNAMIC SCHEDULED DATA-DRIVEN MODELS FOR PARALLEL EXPERT SYSTEMS

 

作者: K. R. TOUT,   D. J. EVANS,  

 

期刊: Parallel Algorithms and Applications  (Taylor Available online 1993)
卷期: Volume 1, issue 4  

页码: 285-301

 

ISSN:1063-7192

 

年代: 1993

 

DOI:10.1080/10637199308915448

 

出版商: Taylor & Francis Group

 

关键词: Data driven;parallel expert system;dynamic scheduling;rulebase compiler

 

数据来源: Taylor

 

摘要:

In this paper we discuss two parallel data-driven models together with their implementations on multiprocessor systems. The parallel models use a dynamic scheduling strategy, and are for a rule-based expert system. All the models are domain independent. To support the use of these models, a “rulebase compiler” has been built to translate a rule base in text format into the data structure needed by the system. The results indicate satisfactory speed up performance for a small number of processors (< 10) and a reasonably large number of rules.

 

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