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Tightness Results for Malleable Task Scheduling Algorithms

  • Ulrich M. Schwarz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4967)

Abstract

Malleable tasks are a way of modelling jobs that can be parallelized to get a (usually sublinear) speedup. The best currently known approximation algorithms for scheduling malleable tasks with precedence constraints are a) 2.62-approximation for certain classes of precedence constraints such as series-parallel graphs [1], and b) 4.72-approximation for general graphs via linear programming [2]. We show that these rates are tight, i.e. there exist instances that achieve the upper bounds.

Keywords

Execution Time Approximation Algorithm Critical Path Precedence Constraint Fractional Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ulrich M. Schwarz
    • 1
  1. 1.Institut für InformatikChristian-Albrechts-Universität zu KielKielGermany

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