Semidefinite Programming for Graph Partitioning with Preferences in Data Distribution

  • Suely Oliveira
  • David Stewart
  • Takako Soma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2565)

Abstract

Graph partitioning with preferences is one of the data distribution models for parallel computer, where partitioning and mapping are generatedto gether. It improves the overall throughput of message trafic by having communication restrictedto processors which are near each other, whenever possible. This model is obtained by associating to each vertex a value which reflects its net preference for being in one partition or another of the recursive bisection process. We have formulated a semidefinite programming relaxation for graph partitioning with preferences andimp lemented efficient subspace algorithm for this model. We numerically comparedou r new algorithm with a standardsem idefinite programming algorithm andsh ow that our subspace algorithm performs better.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Suely Oliveira
    • 1
  • David Stewart
    • 2
  • Takako Soma
    • 1
  1. 1.The Department of Computer ScienceThe University of IowaIowa CityUSA
  2. 2.The Department of MathematicsThe University of IowaIowa CityUSA

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