Explicit parallel structuring for rule-based programming

This paper presents semantically-based explicit parallel structuring for rule-based programming systems. Explicit parallel structuring appears to be necessary since compile-time dependency analysis of sequential programs has not yielded large scale parallelism and run-time analysis for parallelism is restricted by the execution cost of the analysis. Simple language extensions specifying semantics of rules are used to define parallel execution behavior at the rule level. Type definitions for working memory elements are extended to include relationships within and among objects which define the parallelism allowed on instances of object types. The first result presented is that the algorithms implemented by commonly used benchmark rule-based programs contain scalable parallelism. The second result is that much of that parallelism can be captured by simple and modest extensions of rule-based languages which are analogies of models and constructs used for specification of parallel structures in imperative programming languages. A sketch is given for a comprehensive language system which exploits specification of semantics defining parallel structures in both object-definition and executable segments of rule-based programs