Skip to main content
SpringerLink
Log in

On Data Distributions in the Construction of Parallel Programs

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Data distributions have a serious impact on time complexity of parallel programs, developed based on domain decomposition. A new kind of distributions—set distributions, based on set-valued mappings, is introduced. These distributions assign a data object to more than one process. The set distributions can be used especially when the number of processes is greater than the data input size, but, sometimes using set distributions can lead to efficient general parallel algorithms. The work-load properties of these distributions and their impact on the number of communications are discussed. In order to illustrate the implications of data distributions in the construction of parallel programs, some examples are presented. Two parallel algorithms for computation of Lagrange interpolation polynomial are developed, starting from simple distributions and set distributions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. R. C. Agarwal, F. G. Gustavson, S. M. Balle, M. Joshi, and P. Palkar. A High Performance Matrix Multiplication Algorithm for MPPs, PARA'95, pp. 1–7.

  2. E. W. Dijkstra. A Discipline of Programming, Prentice-Hall, Englewood Cliffs, NJ, 1976.

    Google Scholar 

  3. I. Foster. Designing and Building Parallel Programs, Addison-Wesley, 1995.

  4. L. Barbara and J. Guttag. Abstractions and Specification in Program Development, Massachusetts Institute of Technology, 1986.

  5. C. A. R. Hoare. An Axiomatic Basis for Computer Programming, Communications of the ACM, 12(10):576–580, 1969.

    Google Scholar 

  6. L. D. Loyens. A Design Method for Parallel Programs, Technische Universiteit Eindhoven, 1992.

  7. C. Morgan. Programming from Specifications, Prentice Hall, 1990.

  8. D. B. Skillicorn and D. Talia. Models and Languages for Parallel Computation, ACM Computer Surveys, 30(2):123–136, June 1998.

    Google Scholar 

  9. J. R. Smith. The Design and Analysis of Parallel Algorithms, Oxford University Press, 1993.

  10. E. F. Van de Velde. Concurrent Scientific Computing, Spring-Verlag, New-York Inc., 1994.

    Google Scholar 

  11. H. S. Wilf. Algorithms and Complexity, Mason & Prentice Hall, 1985.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Babesç-Bolyai University, Cluj-Napoca, Romania

    Virginia Niculescu

Authors
  1. Virginia Niculescu
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Niculescu, V. On Data Distributions in the Construction of Parallel Programs. The Journal of Supercomputing 29, 5–25 (2004). https://doi.org/10.1023/B:SUPE.0000022570.15441.77

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:SUPE.0000022570.15441.77

Search

Navigation