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BSP Algorithms — “Write Once, Run Anywhere”

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Algorithm Engineering (WAE 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1668))

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Abstract

Scalable computing is rapidly becoming the normal form of computing. In a few years time it may be difficult to buy a computer system which has only one processor. Scalable systems will come in all shapes and sizes, from cheap PC servers and Linux clusters with a small number of processors, up to large, expensive supercomputers with hundreds or thousands of symmetric multiprocessor (SMP) nodes. An important challenge for the research community is to develop a unified framework for the design, analysis and implementation of scalable parallel algorithms.

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References

  1. A V Gerbessiotis and L G Valiant. Direct bulk-synchronous parallel algorithms. Journal of Parallel and Distributed Computing, 22:251–267, 1994.

    Article  Google Scholar 

  2. J M D Hill, B McColl, D C Stefanescu, M W Goudreau, K Lang, S B Rao, T Suel, T Tsantilas, and R H Bisseling. BSPlib: The BSP programming library. Parallel Computing, 24(14):1947–1980, 1998.

    Article  Google Scholar 

  3. W F McColl. Scalable computing. In J van Leeuwen, editor, Computer Science Today: Recent Trends and Developments. LNCS Volume 1000, pages 46–61. Springer-Verlag, 1995.

    Chapter  Google Scholar 

  4. W F McColl. Foundations of time-critical scalable computing. In K Mehlhorn, editor, Fundamentals-Foundations of Computer Science. Proc. 15th IFIP World Computer Congress, 31 August-4 September 1998, Vienna and Budapest, (Invited Paper), pages 93–107. Osterreichische Computer Gesellschaft, 1998.

    Google Scholar 

  5. W F McColl and A Tiskin. Memory-efficient matrix multiplication in the BSP model. Algorithmica, 24(3):287–297, 1999.

    Article  MathSciNet  Google Scholar 

  6. D B Skillicorn, J M D Hill, and W. F. McColl. Questions and answers about BSP. Scientific Programming, 6(3):249–274, Fall 1997.

    Article  Google Scholar 

  7. L G Valiant. A bridging model for parallel computation. Communications of the ACM, 33(8):103–111, 1990.

    Article  Google Scholar 

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© 1999 Springer-Verlag Berlin Heidelberg

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McColl, B. (1999). BSP Algorithms — “Write Once, Run Anywhere”. In: Vitter, J.S., Zaroliagis, C.D. (eds) Algorithm Engineering. WAE 1999. Lecture Notes in Computer Science, vol 1668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48318-7_2

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  • DOI: https://doi.org/10.1007/3-540-48318-7_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66427-7

  • Online ISBN: 978-3-540-48318-2

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