Data-driven parallel production systems

• Published in: IEEE transactions on software engineering Vol. 16; no. 3; pp. 281 - 293
• Main Authors: Gaudiot, J.-L., Sohn, A.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.1990; Institute of Electrical and Electronics Engineers; IEEE Computer Society
• Subjects: Algorithms; Applications; Applied sciences; Architecture; Artificial intelligence; Computer architecture; Computer programming; Computer science; control theory; systems; Conflict resolution; Data structures; Decision making; Delay; Exact sciences and technology; Expert systems; Learning and adaptive systems; Parallel processing; Pattern matching; Production systems; Software engineering; Multiprocessor; Production system; Expert system; Parallel processing; Artificial intelligence; Implementation; Data flow
• ISSN: 0098-5589; 1939-3520
• DOI: 10.1109/32.48936

Much effort has been expended on developing special architectures dedicated to the efficient execution of production systems. While data-flow principles of execution offer the promise of high programmability for numerical computations, it is shown that the data-driven principles can also be applied to symbolic computations. In particular, a mapping of the RETE match algorithm along the line of production systems is considered. Bottlenecks of the RETE match algorithm in a multiprocessor environment are identified and possible solutions are suggested. The modifications to the actor set as well as the program graph design are shown for execution on the tagged data-flow computer. The results of a deterministic simulation of this multiprocessor architecture demonstrate that artificial intelligence production systems can be efficiently mapped on data-driven architectures.< >