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Scientific software libraries for scalable architectures

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Parallel Scientific Computing (PARA 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 879))

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Abstract

Massively parallel processors introduce new demands on software systems with respect to performance, scalability, robustness and portability. The increased complexity of the memory systems and the increased range of problem sizes for which a given piece of software is used, poses serious challenges to software developers. The Connection Machine Scientific Software Library, CMSSL, uses several novel techniques to meet these challenges. The CMSSL contains routines for managing the data distribution and provides data distribution independent functionality. High performance is achieved through careful scheduling of arithmetic operations and data motion, and through the automatic selection of algorithms at run-time. We discuss some of the techniques used, and provide evidence that CMSSL has reached the goals of performance and scalability for an important set of applications.

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Author information

Authors and Affiliations

  1. Thinking Machines Corp., USA

    S. Lennart Johnsson & Kapil K. Mathur

  2. Harvard University, USA

    S. Lennart Johnsson

Authors
  1. S. Lennart Johnsson
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  2. Kapil K. Mathur
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Editor information

Jack Dongarra Jerzy Waśniewski

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© 1994 Springer-Verlag Berlin Heidelberg

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Johnsson, S.L., Mathur, K.K. (1994). Scientific software libraries for scalable architectures. In: Dongarra, J., Waśniewski, J. (eds) Parallel Scientific Computing. PARA 1994. Lecture Notes in Computer Science, vol 879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0030160

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  • DOI: https://doi.org/10.1007/BFb0030160

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58712-5

  • Online ISBN: 978-3-540-49050-0

  • eBook Packages: Springer Book Archive

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