Parallel Knowledge Processing in SNAP.

Dan I. Moldovan, Wing Lee, Changhwa Lin: Parallel Knowledge Processing in SNAP. IEEE Trans. Knowl. Data Eng. 5(1): 65-75(1993)

@article{DBLP:journals/tkde/MoldovanLL93,
  author    = {Dan I. Moldovan and
               Wing Lee and
               Changhwa Lin},
  title     = {Parallel Knowledge Processing in SNAP},
  journal   = {IEEE Trans. Knowl. Data Eng.},
  volume    = {5},
  number    = {1},
  year      = {1993},
  pages     = {65-75},
  ee        = {db/journals/tkde/MoldovanLL93.html},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

The Semantic Network Array Processor (SNAP) is a specialized, highly parallel architecture for knowledge representation and reasoning. The instruction set has been carefully designed to reflect the requirements of semantic network processing. SNAP is a marker propagation architecture, where the passing of markers between cells plays a fundamental role. The movement of markers between cells is controlled by a set of propagation rules. We have implemented various reasoning mechanisms using these propagation rules. A simulator was developed and knowledge processing examples such as inheritance, recognition, classification, and others were tested. By comparing our simulation results with the same examples run on the Connection Machine, we have found that SNAP outperforms the Connection Machine over a broad range of knowledge processing examples by a factor of 1000 or more.

Joint ACM SIGMOD / IEEE Computer Society Anthology

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References

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