Abstract
A synergistic approach utilizing compilation, compaction, and parallelization is described to achieve real-time computing throughput from rule-based expert systems. The methodology involves synthesizing a set of concurrently executable Ada tasks from a knowledge base of rules. Compaction of code size is accomplished by eliminating the overhead associated with inference engine control constructs not utilized by a particular knowledge base. Heuristics are used to customize the generated Ada code for optimum performance gains given the characteristics of the source knowledge base and the target processor. The effectiveness of this approach depends on both the characteristics of the knowledge base and the efficiency of the Ada compiler's task invocation mechanism. A prototype compilation system based on this multifaceted approach has demonstrated speedups in excess of 100* for certain knowledge bases, as well as additional benefits in terms of increased embeddability and maintainability of the knowledge base. >
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