Paper by Erik D. Demaine

Reference:

Erik D. Demaine, Mohammad Ghodsi, MohammadTaghi Hajiaghayi, Amin S. Sayedi-Roshkhar, and Morteza Zadimoghaddam, “Scheduling to Minimize Gaps and Power Consumption”, in Proceedings of the 19th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2007), San Diego, California, June 9–11, 2007, pages 46–54.

BibTeX

@InProceedings{GapScheduling_SPAA2007,
  AUTHOR        = {Erik D. Demaine and Mohammad Ghodsi and
                   MohammadTaghi Hajiaghayi and Amin S. Sayedi-Roshkhar and
                   Morteza Zadimoghaddam},
  TITLE         = {Scheduling to Minimize Gaps and Power Consumption},
  BOOKTITLE     = {Proceedings of the 19th ACM Symposium on Parallelism in
                   Algorithms and Architectures (SPAA 2007)},
  bookurl       = {http://www.spaa-conference.org/},
  ADDRESS       = {San Diego, California},
  MONTH         = {June 9--11},
  YEAR          = 2007,
  PAGES         = {46--54},

  length        = {9 pages},
  papers        = {GapScheduling_JScheduling; SubmodularGapScheduling_SPAA2010},
  doi           = {https://dx.doi.org/10.1145/1248377.1248385},
  dblp          = {https://dblp.org/rec/conf/spaa/DemaineGHSZ07},
  comments      = {This paper is also available from <A HREF="https://doi.org/10.1145/1248377.1248385">ACM</A>.},
}

Abstract:

This paper considers scheduling tasks while minimizing the power consumption of one or more processors, each of which can go to sleep at a fixed cost α. There are two natural versions of this problem, both considered extensively in recent work: minimize the total power consumption (including computation time), or minimize the number of “gaps” in execution. For both versions in a multiprocessor system, we develop a polynomial-time algorithm based on sophisticated dynamic programming. In a generalization of the power-saving problem, where each task can execute in any of a specified set of time intervals, we develop a (1 + (2/3)α)-approximation, and show that dependence on α is necessary. In contrast, the analogous multi-interval gap scheduling problem is set-cover hard (and thus not o(lg n)-approximable), even in the special cases of just two intervals per job or just three unit intervals per job. We also prove several other hardness-of-approximation results. Finally, we give an O(√n)-approximation for maximizing throughput given a hard upper bound on the number of gaps.

Comments:

This paper is also available from ACM.

Length:

The paper is 9 pages.

Availability:

The paper is available in PostScript (335k) and PDF (247k).

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Related papers:

GapScheduling_JScheduling (Scheduling to Minimize Gaps and Power Consumption)

SubmodularGapScheduling_SPAA2010 (Scheduling to Minimize Power Consumption using Submodular Functions)