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Knowledge-based parallelization for distributed memory systems

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Parallel Computation (ACPC 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 591))

Abstract

In current automatic parallelization systems for distributed-memory machines, the user must explicitly specify how the data domain of the sequential program is to be decomposed and distributed across the processors. In this paper, we outline the salient features of a new knowledge-based software tool that provides automatic support for data partitioning. The basic guidelines for the design of the tool are discussed, followed by a description of the adopted partitioning strategy.

The work described in this paper is being carried out as part of the research project “Virtual Shared Memory for Multiprocessor Systems with Distributed Memory” funded by the Austrian Research Foundation (FWF) under the grant number P7576-TEC. The authors assume all responsibility for the contents.

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Authors and Affiliations

  1. Department of Statistics and Computer Science, University of Vienna, Rathausstrasse 19/II/3, A-1010, Vienna, Austria

    Barbara M. Chapman & Heinz M. Herbeck

Authors
  1. Barbara M. Chapman
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  2. Heinz M. Herbeck
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Hans P. Zima

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© 1992 Springer-Verlag Berlin Heidelberg

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Chapman, B.M., Herbeck, H.M. (1992). Knowledge-based parallelization for distributed memory systems. In: Zima, H.P. (eds) Parallel Computation. ACPC 1991. Lecture Notes in Computer Science, vol 591. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55437-8_72

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  • DOI: https://doi.org/10.1007/3-540-55437-8_72

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55437-0

  • Online ISBN: 978-3-540-47073-1

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