DYNAMIC SCHEDULED DATA-DRIVEN MODELS FOR PARALLEL EXPERT SYSTEMS
Kifah R. Tout, David J. Evans · International Journal of Parallel Emergent and Distributed Systems · 1993
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.