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An efficient scheme for fine-grain software pipelining

  • Implementation Issues For Novel Architectures And Languages
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CONPAR 90 — VAPP IV (VAPP 1990, CONPAR 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 457))

Abstract

Dataflow software pipelining was proposed as a means of structuring fine-grain parallelism and has been studied mostly under an idealized dataflow architecture model with infinite resources[7]. In this paper, we address some issues of software pipelining under a realistic architecture model with finite resources. A general framework for fine-grain code scheduling in pipelined machines is developed which simultaneously addresses both time and space efficiency issues for loops typically found in general-purpose scientific computations. This scheduling method exploits fine-grain parallelism through a loop optimization technique which limitedly balances the program graph at compile time, while the instruction-level scheduling is done dynamically at runtime in a data-driven manner.

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Author information

Authors and Affiliations

  1. School of Computer Science, McGill University, 3480 University, H3A 2A7, Montréal, Québec

    Guang R. Gao

  2. Centre de recherche informatique de Montréal, McGill University, Canada

    Herbert H. J. Hum

  3. 1550 boul. de Maisonneuve O., H3G 1N2, Montréal, Québec

    Herbert H. J. Hum

  4. School of Computer Science, McGill University, Canada

    Yue-Bong Wong

Authors
  1. Guang R. Gao
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  2. Herbert H. J. Hum
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  3. Yue-Bong Wong
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Editor information

Helmar Burkhart

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© 1990 Springer-Verlag Berlin Heidelberg

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Gao, G.R., Hum, H.H.J., Wong, YB. (1990). An efficient scheme for fine-grain software pipelining. In: Burkhart, H. (eds) CONPAR 90 — VAPP IV. VAPP CONPAR 1990 1990. Lecture Notes in Computer Science, vol 457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53065-7_147

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  • DOI: https://doi.org/10.1007/3-540-53065-7_147

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53065-7

  • Online ISBN: 978-3-540-46597-3

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