PARTES: A partitioning scheme for parallel matching

Focuses on the partitioning of rules for parallel matching in a production system. The approach, called PARTES, applies the min-cut technique to a dataflow discrimination network (DDN) that represents the antecedents of the rules. The goal is to maximize the sharing of memory nodes within a partition while minimizing the duplication of nodes across partitions. The authors illustrate the technique using a cost model based on shared memory nodes defined in a DDN created by the Rete algorithm. A generalization to any other algorithm utilizing a DDN is straightforward. A performance analysis is provided to show the effectiveness of PARTES.

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