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High-level languages for parallel scientific computing

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SOFSEM '95: Theory and Practice of Informatics (SOFSEM 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1012))

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Abstract

Highly parallel scalable multiprocessing systems are powerful tools for solving large-scale scientific and engineering problems. Languages such as Vienna Fortran and High Performance Fortran (HPF) have been introduced to allow the programming of these machines at a relatively high level of abstraction, based on the data-parallel Single-Program-Multiple-Data (SPMD) model. Their main features focus on the distribution of data across the processors of a machine. In this paper, we outline the state-of-the-art in this area and provide a detailed description of HPF. A significant weakness of current HPF is its lack of support for many advanced applications, which require irregular data distributions, dynamic load balancing, or task parallelism. We introduce HPF+, an extension of HPF based on Vienna Fortran, that addresses these problems and provides the required functionality.

The work described in this paper was partially supported by the Austrian Research Foundation (FWF Grant P8989-PHY) and by the Austrian Ministry for Science and Research (BMWF Grant GZ 308.9281- IV/3/93). This research was also supported by the National Aeronautics and Space Administration under NASA Contract No. NAS1-18605, while the authors were in residence at ICASE, NASA Langley Research Center, Hampton, VA 23681.

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Author information

Authors and Affiliations

  1. Institute for Software Technology and Parallel Systems, University of Vienna, Liechtensteinstr. 22, A-1090, Vienna, Austria

    Barbara Chapman & Hans Zima

  2. NASA Langley Research Center, ICASE, MS 132C, 23681, Hampton, VA, USA

    Piyush Mehrotra

Authors
  1. Barbara Chapman
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  2. Piyush Mehrotra
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  3. Hans Zima
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Miroslav Bartosek Jan Staudek Jirí Wiedermann

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© 1995 Springer-Verlag Berlin Heidelberg

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Chapman, B., Mehrotra, P., Zima, H. (1995). High-level languages for parallel scientific computing. In: Bartosek, M., Staudek, J., Wiedermann, J. (eds) SOFSEM '95: Theory and Practice of Informatics. SOFSEM 1995. Lecture Notes in Computer Science, vol 1012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60609-2_14

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  • DOI: https://doi.org/10.1007/3-540-60609-2_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60609-3

  • Online ISBN: 978-3-540-48463-9

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