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Dependence driven execution for data parallelism

  • Run Time Control of Parallelism
  • Conference paper
  • First Online:
Languages and Compilers for Parallel Computing (LCPC 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1239))

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Abstract

This paper proposes an efficient run-time system to schedule general nested loops on multiprocessors. The work extends existing one-dimensional loop scheduling strategies such as static scheduling, affinity scheduling and various dynamic scheduling methods. The extensions are twofold. First, multiple independent loops as found in different branches of parbegin/parend constructs can be scheduled simultaneously. Secondly, multidimensional loops with dependencies and conditions can be aggressively scheduled. The ability to schedule multidimensional loops with dependencies is made possible by providing a dependence vector as an input to the scheduler. Based on this application-specific input, a continuation-passing run-time system using non-blocking threads efficiently orchestrates the parallelism on shared memory MIMD and DSM multi-computers. The run-time system uses a dependence-driven execution which is similar to data-driven and message-driven executions in that it is asynchronous. This asynchrony allows a high degree of parallelism.

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Authors and Affiliations

  1. University of Colorado, Campus Box 430, 80309, Boulder, Colorado

    Suvas Vajracharya & Dirk Grunwald

Authors
  1. Suvas Vajracharya
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  2. Dirk Grunwald
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Editor information

David Sehr Utpal Banerjee David Gelernter Alex Nicolau David Padua

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© 1997 Springer-Verlag Berlin Heidelberg

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Vajracharya, S., Grunwald, D. (1997). Dependence driven execution for data parallelism. In: Sehr, D., Banerjee, U., Gelernter, D., Nicolau, A., Padua, D. (eds) Languages and Compilers for Parallel Computing. LCPC 1996. Lecture Notes in Computer Science, vol 1239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017276

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  • DOI: https://doi.org/10.1007/BFb0017276

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63091-3

  • Online ISBN: 978-3-540-69128-0

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