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On the distributed implementation of aggregate data structures by program transformation

  • Gabriele Keller
  • Manuel M. T. Chakravarty
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1586)

Abstract

A critical component of many data-parallel programming languages are operations that manipulate aggregate data structures as a whole—this includes Fortran 90, Nesl, and languages based on BMF. These operations are commonly implemented by a library whose routines operate on a distributed representation of the aggregate structure; the compiler merely generates the control code invoking the library routines and all machine-dependent code is encapsulated in the library. While this approach is convenient, we argue that by breaking the abstraction enforced by the library and by presenting some of internals in the form of a new intermediate language to the compiler back-end, we can optimize on al levels of the memory hierarchy and achieve more flexible data distribution. The new intermediate language allows us to present these optimisations elegantly as program transformations. We report on first results obtained by our approach in the implementation of nested data parallelism on distributed-memory machines.

Keywords

Local Computation Local Operation Aggregate Structure Memory Hierarchy Program Transformation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • Gabriele Keller
    • 1
  • Manuel M. T. Chakravarty
    • 2
  1. 1.Fachbereich InformatikTechnische Universität BerlinGermany
  2. 2.Inst. of Inform. Sciences and ElectronicsUniversity of TsukubaJapan

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