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Lessons learned from implementing BSP

  • Jonathan M. D. Hill
  • David B. Skillicorn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1225)

Abstract

We focus on two criticisms of Bulk Synchronous Parallelism (BSP): that delaying communication until specific points in a program causes poor performance, and that frequent barrier synchronisations are too expensive for high-performance parallel computing. We show that these criticisms are misguided, not just about BSP but about parallel programming in general, because they are based on misconceptions about the origins of poor performance. The main implication for parallel programming is that higher levels of abstraction do not only make software construction easier—they also make high-performance implementation easier.

Keywords

Shared Memory Delivery Time Runtime System Cache Coherence Barrier Synchronisation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    M.W. Goudreau, J.M.D. Hill, K. Lang, W.F. McColl, S.D. Rao, D.C. Stefanescu, T. Suel, and T. Tsantilas. A proposal for a BSP Worldwide standard. BSP Worldwide, http://www.bsp-worldwide.org/, April 1996.Google Scholar
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    D.B. Skillicorn, J.M.D. Hill, and W.F. McColl. Questions and answers about BSP. Technical Report TR-15-96, Oxford University Computing Laboratory, August 1996.Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Jonathan M. D. Hill
    • 1
  • David B. Skillicorn
    • 2
  1. 1.Computing LaboratoryOxford UniversityUK
  2. 2.Department of Computing and Information ScienceQueen's UniversityKingstonCanada

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