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Using Projection Analysis in Compiling Lazy Functional Programs
- In Proceedings of the 1990 ACM Conference on Lisp and Functional Programming
, 1990
"... Projection analysis is a technique for finding out information about lazy functional programs. We show how the information obtained from this analysis can be used to speed up sequential implementations, and introduce parallelism into parallel implementations. The underlying evaluation model is evalu ..."
Abstract
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Cited by 15 (6 self)
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Projection analysis is a technique for finding out information about lazy functional programs. We show how the information obtained from this analysis can be used to speed up sequential implementations, and introduce parallelism into parallel implementations. The underlying evaluation model is evaluation transformers, where the amount of evaluation that is allowed of an argument in a function application depends on the amount of evaluation allowed of the application. We prove that the transformed programs preserve the semantics of the original programs. Compilation rules, which encode the information from the analysis, are given for sequential and parallel machines. 1 Introduction A number of analyses have been developed which find out information about programs. The methods that have been developed fall broadly into two classes, forwards analyses such as those based on the ideas of abstract interpretation (e.g. [9, 18, 19, 7, 17, 12, 4, 20]), and backward analyses such as those based...
Implementing the Evaluation Transformer Model of Reduction on Parallel Machines
, 1991
"... The evaluation transformer model of reduction generalises 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 d ..."
Abstract
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Cited by 7 (1 self)
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The evaluation transformer model of reduction generalises 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-knon G-machine, a machine for executing lazy functional programs.

