Probabilistic Rotation: Scheduling Graphs with Uncertain Execution Time

  • Authors:
  • Sissades Tongsima;Chantana Chantrapornchai;Edwin Hsing-Mean Sha;Nelson L. Passos

  • Affiliations:
  • -;-;-;-

  • Venue:
  • ICPP '97 Proceedings of the international Conference on Parallel Processing
  • Year:
  • 1997

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Abstract

This paper proposes an algorithm called probabilistic rotation scheduling which takes advantage of loop pipelining to schedule tasks with uncertain times to a parallel processing system. These tasks normally occur when conditional instructions are employed and/or inputs of the tasks influence the computation time. We show that based on our loop scheduling algorithm the length of the resulting schedule can be guaranteed to be satisfied for a given probability. The experiments show that the resulting schedule length for a given probability of confidence can be significantly better than the schedules obtained by worst-case or average-case scenario.