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Issue No.01 - February (1993 vol.5)
pp: 65-75
ABSTRACT
<p>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. Various reasoning mechanisms were implemented using these propagation rules. A simulator was developed, and knowledge processing examples, such as inheritance, recognition, and classification, were tested. By comparing the simulation results with the same examples run on the Connection Machine, it was found that SNAP outperforms the Connection Machine over a broad range of knowledge processing examples by a factor of 1000 or more.</p>
INDEX TERMS
semantic network array processor; highly parallel architecture; knowledge representation; reasoning; instruction set; marker propagation architecture; markers; reasoning mechanisms; simulator; inheritance; recognition; classification; Connection Machine; digital simulation; instruction sets; parallel architectures; semantic networks
CITATION
D.I. Moldovan, W. Lee, C. Lin, "Parallel Knowledge Processing on SNAP", IEEE Transactions on Knowledge & Data Engineering, vol.5, no. 1, pp. 65-75, February 1993, doi:10.1109/69.204092
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