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The Multi-architecture Performance of the Parallel Functional Language GpH

  • Philip W. Trinder
  • Hans-Wolfgang Loidl
  • Ed. BarryJr.
  • M. Kei Davis
  • Kevin Hammond
  • Ulrike Klusik
  • Simon L. Peyton Jones
  • Álvaro J. Rebón Portillo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1900)

Abstract

In principle, functional languages promise straightforward architecture-independent parallelism, because of their high level descrip- tion of parallelism, dynamic management of parallelism and deterministic semantics. However, these language features come at the expense of a so- phisticated compiler and/or runtime-system. The problem we address is whether such an elaborate system can deliver acceptable performance on a variety of parallel architectures. In particular we report performance measurements for the GUM runtime-system on eight parallel architec- tures, including massively parallel, distributed-memory, shared-memory and workstation networks.

Keywords

Parallel Architecture Functional Language Relative Speedup Absolute Speedup Dynamic Resource Allocation 
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 Berlin Heidelberg 2000

Authors and Affiliations

  • Philip W. Trinder
    • 1
  • Hans-Wolfgang Loidl
    • 1
  • Ed. BarryJr.
  • M. Kei Davis
    • 2
  • Kevin Hammond
    • 3
  • Ulrike Klusik
    • 4
  • Simon L. Peyton Jones
    • 5
  • Álvaro J. Rebón Portillo
    • 3
  1. 1.Heriot-Watt UniversityEdinburghUK
  2. 2.Los Alamos National LaboratoryUSA
  3. 3.University of St. AndrewsUK
  4. 4.Philipps-University MarburgGermany
  5. 5.Microsoft Research LtdCambridgeUK

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