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A Framework for Global Communication Analysis and Optimizations

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Compiler Optimizations for Scalable Parallel Systems

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1808))

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Abstract

Distributed memory architectures have become popular as a viable and cost-effective method of building scalable parallel computers. However, the absence of global address space, and consequently, the need for explicit message passing among processes makes these machines very difficult to program. This has motivated the design of languages like High Performance Fortran [14], which allow the programmer to write sequential or shared-memory parallel programs that are annotated with directives specifying data decomposition. The compilers for these languages are responsible for partitioning the computation, and generating the communication necessary to fetch values of nonlocal data referenced by a processor. A number of such prototype compilers have been developed [3, 6, 19, 23, 29, 30, 33, 34, 43].

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Author information

Authors and Affiliations

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

    Manish Gupta

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  1. Manish Gupta
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Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GA, 30332, USA

    Santosh Pande

  2. Department of ECECS, University of Cincinnati, P.O. Box 210030, Cincinnati, OH, 45221-0030, USA

    Dharma P. Agrawal

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© 2001 Springer-Verlag Berlin Heidelberg

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Gupta, M. (2001). A Framework for Global Communication Analysis and Optimizations. In: Pande, S., Agrawal, D.P. (eds) Compiler Optimizations for Scalable Parallel Systems. Lecture Notes in Computer Science, vol 1808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45403-9_14

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  • DOI: https://doi.org/10.1007/3-540-45403-9_14

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  • Print ISBN: 978-3-540-41945-7

  • Online ISBN: 978-3-540-45403-8

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