[comp.ai] Guaranteeing Serializable Results in Parallel Production Systems

finin@prc.unisys.com (Tim Finin) (03/25/89)

				  AI SEMINAR
			 UNISYS PAOLI RESEARCH CENTER
				       
				       
       Guaranteeing Serializable Results in Parallel Production Systems
				       
				 Jim Schmolze
			       Computer Science
			       Tufts University
                             schmolze@cs.tufts.edu

To speed up production systems, researchers have studied how to execute many
rules simultaneously.  Unfortunately, such systems can yield results that are
impossible for a serial system to produce, leading to erroneous behaviors.  We
present algorithms that prevent all non-serializable effects for parallel
production systems that execute many rules simultaneously.  Our framework is
taken from [1] and improves upon their solution.  The practical advantages of
these strategies is demonstrated using estimates from a large production
system, the Manhattan Mapper [2].

  [1] T. Ishida and S.J. Stolfo.  "Towards the parallel execution of
      rules in production system programs."  In Proceedings of the
      International Conference on Parallel Processing, 1985.

  [2] L. Lerner and J. Cheng.  "The Manhattan Mapper expert production
      system."  Tech. Report, Computer Science, Columbia , May 1983.

				       
			11:00 am, Monday April 3, 1989
			     BIC Conference Room
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