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Implementing the evaluation transformer model of reduction on parallel machines

Part of: JFP Research Articles

Published online by Cambridge University Press:  07 November 2008

G. L. Burn
G. L. Burn
Affiliation:
Department of Computing, Imperial College of Science, Technology and Medicine, London SW7 2BZ, UK
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Abstract

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The evaluation transformer model of reduction generalizes lazy evaluation in two ways: it can start the evaluation of expressions before their first use, and it can evaluate expressions further than weak head normal form. Moreover, the amount of evaluation required of an argument to a function may depend on the amount of evaluation required of the function application. It is a suitable candidate model for implementing lazy functional languages on parallel machines.

In this paper we explore the implementation of lazy functional languages on parallel machines, both shared and distributed memory architectures, using the evaluation transformer model of reduction. We will see that the same code can be produced for both styles of architecture, and the definition of the instruction set is virtually the same for each style. The essential difference is that a distributed memory architecture has one extra node type for non-local pointers, and instructions which involve the value of such nodes need their definitions extended to cover this new type of node.

To make our presentation accessible, we base our description on a variant of the well-known G-machine, an abstract machine for executing lazy functional programs.

Type
Articles
Information
Journal of Functional Programming , Volume 1 , Issue 3 , July 1991 , pp. 329 - 366
Copyright
Copyright © Cambridge University Press 1991

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