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Polynomial time scheduling of low level computer vision algorithms on networks of heterogeneous machines

  • Adam R. Nolan
  • Bryan Everding
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 966)

Abstract

Defining an optimal schedule for arbitrary algorithms on a network of heterogeneous machinesis an NP complete problem. This paper focuses on data parallel deterministic neighborhood computer vision algorithms. This focus enables the polynomial time definition of a schedule which minimizes the distributed execution time by overlapping computation and communication cycles on the network. The scheduling model allows for any speed machine to participate in the concurrent computation but makes theassumption of a master/slave control mechanism using a linear communication network. Several vision algorithms are presented and described in terms of the scheduling model parameters. The theoretical speed up of these algorithms is discussed and empirical data is presented and compared to theoretical results.

Keywords

Computer Vision Heterogeneous Architectures Scheduling Distributed Algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Adam R. Nolan
    • 1
  • Bryan Everding
    • 1
  1. 1.Artificial Intelligence and Computer Vision LabUniversity of CincinnatiUSA

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