Skip to main content

Dynamic load balancing with a spectral bisection algorithm for the constrained graph partitioning problem

  • Conference paper
  • First Online:
High-Performance Computing and Networking (HPCN-Europe 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 919))

Included in the following conference series:

Abstract

We present a spectral bisection algorithm for the constrained graph partitioning problem, i.e. a graph partitioning problem in which some of the vertices of the graph are assigned a priori to given subsets. We show how this algorithm can be used for dynamic load balancing of grid-oriented problems on dynamically changing grids.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. T. Barnard and H. D. Simon. Fast multilevel implementation of recursive spectral bisection for partitioning unstructured problems. Concurrency: Practice and Experience, 6(2):101–117, April 1994.

    Google Scholar 

  2. W. Gander, G. H. Golub, and U. von Matt. A constrained eigenvalue problem. Linear Algebra and its Applications, 114/115:815–839, 1989.

    Article  Google Scholar 

  3. B. Hendrickson and R. Leland. A multilevel algorithm for partitioning graphs. Technical Report SAND93-1301, Sandia National Labs, October 1993.

    Google Scholar 

  4. W. F. Mitchell. Refinement tree based partitioning for adaptive grids. In D. H. Bailey et al., editors, Parallel Processing for Scientific Computing, pages 587–592. SIAM, 1995.

    Google Scholar 

  5. A. Pothen, H. D. Simon, and K.-P. Liou. Partitioning sparse matrices with eigenvectors of graphs. SIAM J. Matrix Anal. Appl., 11(3):430–452, 1990.

    Article  MathSciNet  Google Scholar 

  6. E. Pramono, H. D. Simon, and A. Sohn. Dynamic load balancing for finite element calculations on parallel computers. In D. H. Bailey et al., editors, Parallel Processing for Scientific Computing, pages 599–604. SIAM, 1995.

    Google Scholar 

  7. H. D. Simon. Partitioning of unstructured problems for parallel processing. Computing Systems in Engineering, 2(2/3):135–148, 1991.

    Google Scholar 

  8. R. Van Driessche and D. Roose. A spectral algorithm for constrained graph partitioning I: The bisection case. TW Report 216, Department of Computer Science, Katholieke Universiteit Leuven, Belgium, October 1994.

    Google Scholar 

  9. R. Van Driessche and D. Roose. An improved spectral bisection algorithm and its application to dynamic load balancing. Parallel Computing, 21:29–48, 1995.

    MathSciNet  Google Scholar 

  10. R. Van Driessche and D. Roose. A graph contraction algorithm for the fast calculation of the Fiedler vector of a graph. In D. H. Bailey et al., editors, Parallel Processing for Scientific Computing, pages 621–626. SIAM, 1995.

    Google Scholar 

  11. C. Walshaw, M. Cross, and M. G. Everett. A parallelisable algorithm for optimising unstructured mesh partitions. Math. research report, School of Mathematics, Statistics & Scientific Computing, Univ. of Greenwich, London, January 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Bob Hertzberger Giuseppe Serazzi

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Van Driessche, R., Roose, D. (1995). Dynamic load balancing with a spectral bisection algorithm for the constrained graph partitioning problem. In: Hertzberger, B., Serazzi, G. (eds) High-Performance Computing and Networking. HPCN-Europe 1995. Lecture Notes in Computer Science, vol 919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046658

Download citation

  • DOI: https://doi.org/10.1007/BFb0046658

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59393-5

  • Online ISBN: 978-3-540-49242-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics