Journal
SIAM JOURNAL ON COMPUTING
Volume 37, Issue 2, Pages 401-412Publisher
SIAM PUBLICATIONS
DOI: 10.1137/S0097539701385995
Keywords
scheduling; malleable tasks; polynomial approximation; performance guarantee
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A malleable task is a computational unit that may be executed on any arbitrary number of processors, whose execution time depends on the amount of resources allotted to it. This paper presents a new approach for scheduling a set of independent malleable tasks which leads to a worst case guarantee of (3)/(2) + epsilon for the minimization of the parallel execution time for any fixed epsilon > 0. The main idea of this approach is to focus on the determination of a good allotment and then to solve the resulting problem with a fixed number of processors by a simple scheduling algorithm. The first phase is based on a dual approximation technique where the allotment problem is expressed as a knapsack problem for partitioning the set of tasks into two shelves of respective heights 1 and (1)/(2).
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