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A Method of Vector Processing for Shared Symbolic Data

Kanada, Y., Parallel Computing, Vol. 19, 1993, pp. 1155-1175.

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Abstract: Conventional processing techniques for pipelined vector processors such as the Cray-XMP, or data-parallel computers, such as the Connection Machines, are generally applied only to independent multiple data prcessing. This paper describes a vector processing method for multiple processings including parallel rewriting of dynamic data strutures with shared elements, and for mutiple procesings that may rewrite the same data item multiple times. This method enables vector processing when entering mutiple data items into a hash table, address calculation sorting, and many other algorithms that handle lists, trees, graphs and other types of symbolic data structures. This method is aplied to several algorithms; consequently, the peformance is improved by a fator of ten on a Hitachi S-810.

[No English abstract is available.]

Introduction to this research theme: Logic/Symbolic Vector Processing

Keywords: Vectorization of symbol processing, Vectorized symbol processing, Parallel symbol processing, Supercomputing, Super symbol processing, Parallel processing, Vector processing

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