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Task Farm Computations in Java

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High Performance Computing and Networking (HPCN-Europe 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1823))

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Abstract

We describe an experiment in the development of an efficient Java support for task farm computations. The support allows Java programmers to rapidly develop parallel task farm applications starting from the plain sequential code. The target architecture we considered during the development of the support is a cluster of Unix workstations. We show experimental results that demonstrate the feasibility of the approach and we discuss the performance of this Java task farm support used on a typical workstation cluster. The task farm support discussed here is the first step towards the implementation of a full skeleton based parallel programming environment in Java.

This work has been partially funded by the Italian projects MOSAICO and PQE2000

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Pisa, Italy

    M. Danelutto

Authors
  1. M. Danelutto
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Academic Computer Center CYFRONET, University of Mining and Metallurgy (AGH), al. Mickiewicza 30, 30-059, Cracow, Poland

    Marian Bubak

  2. Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Universiteit van Amsterdam, 1098 SJ, Amsterdam, The Netherlands

    Hamideh Afsarmanesh  & Bob Hertzberger  & 

  3. California Institute of Technology, Caltech 158-79, Pasadena, CA, 91125, USA

    Roy Williams

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© 2000 Springer-Verlag Berlin Heidelberg

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Danelutto, M. (2000). Task Farm Computations in Java. In: Bubak, M., Afsarmanesh, H., Hertzberger, B., Williams, R. (eds) High Performance Computing and Networking. HPCN-Europe 2000. Lecture Notes in Computer Science, vol 1823. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45492-6_38

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  • DOI: https://doi.org/10.1007/3-540-45492-6_38

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67553-2

  • Online ISBN: 978-3-540-45492-2

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