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ASC: An Associative-Computing Paradigm
November 1994 (vol. 27 no. 11)
pp. 19-25

Today's increased computing speeds allow conventional sequential machines to effectively emulate associative computing techniques. We present a parallel programming paradigm called ASC (ASsociative Computing), designed for a wide range of computing engines. Our paradigm has an efficient associative-based, dynamic memory-allocation mechanism that does not use pointers. It incorporates data parallelism at the base level, so that programmers do not have to specify low-level sequential tasks such as sorting, looping and parallelization. Our paradigm supports all of the standard data-parallel and massively parallel computing algorithms. It combines numerical computation (such as convolution, matrix multiplication, and graphics) with nonnumerical computing (such as compilation, graph algorithms, rule-based systems, and language interpreters). This article focuses on the nonnumerical aspects of ASC.

Citation:
Jerry Potter, Johnnie Baker, Stephen Scott, Arvomd Bansal, Chokchai Leangsuksun, Chandra Asthagiri, "ASC: An Associative-Computing Paradigm," Computer, vol. 27, no. 11, pp. 19-25, Nov. 1994, doi:10.1109/2.330039
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