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Open Access Publications from the University of California

A data-driven model for parallel interpretation of logic programms [sic]

  • Author(s): Bic, Lubomir
  • et al.

The main objective of this paper is to present a model of computation which permits logic programs to be executed on a highly-parallel computer architecture. It demonstrates how logic programs may be converted into collections of dataflow graphs in which resolution is viewed as a process of finding matches between certain graph templates and portions of the dataflow graphs. This graph fitting process is carried out by tokens propogating asynchronously through the dataflow graph; thus computation is entirely data-driven, without the need for any centralized control. It is shown that at the implementation level the proposed model is very similar to a general dataflow system and hence a dataflow architecture could easily be extended to support the proposed model.

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