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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