LISP and Symbolic Computation

, Volume 2, Issue 3–4, pp 179–396 | Cite as

The interprocedural analysis and automatic parallelization of Scheme programs

  • Williams Ludwell HarrisonIII
Article

Abstract

Lisp and its descendants are among the most important and widely used of programming languages. At the same time, parallelism in the architecture of computer systems is becoming commonplace. There is a pressing need to extend the technology of automatic parallelization that has become available to Fortran programmers of parallel machines, to the realm of Lisp programs and symbolic computing. In this paper we present a comprehensive approach to the compilation of Scheme programs for shared-memory multiprocessors. Our strategy has two principal components:interprocedural analysis andprogram restructuring. We introduceprocedure strings andstack configurations as a framework in which to reason about interprocedural side-effects and object lifetimes, and develop a system of interprocedural analysis, using abstract interpretation, that is used in the dependence analysis and memory management of Scheme programs. We introduce the transformations ofexit-loop translation andrecursion splitting to treat the control structures of iteration and recursion that arise commonly in Scheme programs. We propose an alternative representation for s-expressions that facilitates the parallel creation and access of lists. We have implemented these ideas in a parallelizing Scheme compiler and run-time system, and we complement the theory of our work with “snapshots” of programs during the restructuring process, and some preliminary performance results of the execution of object codes produced by the compiler.

Keywords

Interprocedural Analysis Abstract Interpretation Automatic Parallelization Program Transformation Parallel Processing Symbolic Computation Lisp Scheme 

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Copyright information

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • Williams Ludwell HarrisonIII
    • 1
  1. 1.Center for Supercomputing Research and DevelopmentUniversity of Illinois at Urbana-Champaign 305 Talbot LaboratoryUrbana

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