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2002•Unpublished venueRequires access

Parallel history sensitive computations in dataflow architecture

J.H. Park, K. M. George

Open publisher page 1 citations

Abstract

This paper addresses the history sensitive computation problem in dataflow architecture. Current solutions use memory which is going a step backwards to Von Neumann model of computers. Furthermore, these solutions are not suitable for exploiting parallelism. In this paper, a new memoryless solution is reviewed and approaches based on forwarding, pipelining, and loop unfolding to maximize its parallel processing are presented. Forwarding mechanisms are presented for both static and dynamic dataflow environments.

About this research paper

What this paper is about

This paper addresses the history sensitive computation problem in dataflow architecture. Current solutions use memory which is going a step backwards to Von Neumann model of computers. Furthermore, these solutions are not suitable for exploiting parallelism. In this paper, a new memoryless solution is reviewed and approaches based on forwarding, pipelining, and loop unfolding to maximize its parallel processing are presented. Forwarding mechanisms are presented for both static and dynamic dataflow environments.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper addresses the history sensitive computation problem in dataflow architecture. Current solutions use memory which is going a step backwards to Von Neumann model of computers. Furthermore, these solutions are not suitable for exploiting parallelism. In this paper, a new memoryless solution is reviewed and approaches based on forwarding, pipelining, and loop unfolding to maximize its parallel processing are presented. Forwarding mechanisms are presented for both static and dynamic dataflow environments.

Key concepts: Dataflow, Dataflow architecture, Computer science, Parallel computing, Computation, Von Neumann architecture, Model of computation, Parallelism (grammar)

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