ASC: An Associative-Computing Paradigm

Authors:
Jerry Potter;Johnnie Baker;Stephen Scott;Arvomd Bansal;Chokchai Leangsuksun;Chandra Asthagiri
Affiliations:
-;-;-;-;-;-
Venue:
Computer
Year:
1994

Citing 2
Cited 15

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Implementing Associative Processing: Rethinking EarlierArchitectural Decisions

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Timing for Associative Operations on the MASC Model

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Implementing Associative Search and Responder Resolution

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A Multiple Associative Model to Support Branches in Data Parallel Applications using the Manager-Worker Paradigm

IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 14 - Volume 15
IT education in the flattening world

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Relating the power of the Multiple Associative Computing (MASC) model to that of reconfigurable bus-based models

Journal of Parallel and Distributed Computing
A Simple Implementation of Dijkstra's Shortest Path Algorithm on Associative Parallel Processors

Fundamenta Informaticae
Comparisons of air traffic control implementations on an associative processor with a MIMD and consequences for parallel computing

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AC-DIMM: associative computing with STT-MRAM

Proceedings of the 40th Annual International Symposium on Computer Architecture
Fine-grained parallel implementations for SWAMP+ Smith-Waterman alignment

Parallel Computing
A gentle introduction to the associative computing (ASC) model of parallel computation

Journal of Computing Sciences in Colleges

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Abstract

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.