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International Workshop on Languages and Compilers for Parallel Computing

LCPC 2000: Languages and Compilers for Parallel Computing pp 97–111Cite as

Extending Scalar Optimizations for Arrays

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2017))

Abstract

Traditional techniques for array analysis do not provide dataflow information, and thus traditional dataflow-based scalar optimizations have not been applied to array elements. A number of techniques have recently been developed for producing information about array dataflow, raising the possibility that dataflow-based optimizations could be applied to array elements. In this paper, we show that the value-based dependence relations produced by the Omega Test can be used as a basis for generalizations of several scalar optimizations.

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Author information

Authors and Affiliations

  1. Haverford College, Haverford, PA, 19041, USA

    David Wonnacott

Authors
  1. David Wonnacott
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Editor information

Editors and Affiliations

  1. IBM T.J.Watson Research Center, P.O. Box 218, Yorktown Heights, NY, 10598, USA

    Samuel P. Midkiff , José E. Moreira , Manish Gupta  & Siddhartha Chatterjee , ,  & 

  2. Computer Science and Engineering, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0114, USA

    Jeanne Ferrante

  3. Department of Computer Science, University of North Carolina, Chapel Hill, NC, 27599-3175, USA

    Jan Prins

  4. Department of Computer Science, University of Maryland, College Park, MD, 20742, USA

    William Pugh  & Chau-Wen Tseng  & 

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© 2001 Springer-Verlag Berlin Heidelberg

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Wonnacott, D. (2001). Extending Scalar Optimizations for Arrays. In: Midkiff, S.P., et al. Languages and Compilers for Parallel Computing. LCPC 2000. Lecture Notes in Computer Science, vol 2017. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45574-4_7

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  • DOI: https://doi.org/10.1007/3-540-45574-4_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42862-6

  • Online ISBN: 978-3-540-45574-5

  • eBook Packages: Springer Book Archive

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