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Managing side effects on shared data

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Book cover Parallel Symbolic Computing: Languages, Systems, and Applications (PSC 1992)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 748))

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Abstract

We are developing a toolbox for writing symbolic programs that may be executed on sequential and parallel machines without modification. The toolbox is designed for use by programmers who are not experienced in parallel programming, and consists of parallelism abstractions and data-sharing abstractions. Parallelism abstractions represent common, time-consuming operations that offer good speedup potentials for parallel implementations. Data-sharing abstractions support common side-effecting operations on shared objects, simplifying the coding of a large class of algorithms that modify shared data structures in a parallel implementation. In this paper we describe the data-sharing abstractions of the toolbox, and show how the toolbox may be used to construct efficient parallel programs without exposing the programmer to low-level parallel programming details, which are hidden by the toolbox implementation.

Ho and Hilfinger are supported by NSF Grant CCR-8451213.

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Authors and Affiliations

  1. Computer Science Division, University of California at Berkeley, USA

    Kinson Ho & Paul N. Hilfinger

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  1. Kinson Ho
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  2. Paul N. Hilfinger
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Robert H. Halstead Jr. Takayasu Ito

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© 1993 Springer-Verlag Berlin Heidelberg

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Ho, K., Hilfinger, P.N. (1993). Managing side effects on shared data. In: Halstead, R.H., Ito, T. (eds) Parallel Symbolic Computing: Languages, Systems, and Applications. PSC 1992. Lecture Notes in Computer Science, vol 748. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0018654

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  • DOI: https://doi.org/10.1007/BFb0018654

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57396-8

  • Online ISBN: 978-3-540-48133-1

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