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Power-aware scheduling for makespan and flow

Published:30 July 2006Publication History

ABSTRACT

We consider offline scheduling algorithms that incorporate speed scaling to address the bicriteria problem of minimizing energy consumption and a scheduling metric. For makespan, we give linear-time algorithms to compute all non-dominated solutions for the general uniprocessor problem and for the multiprocessor problem when every job requires the same amount of work. We also show that the multiprocessor problem becomes NP-hard when jobs can require different amounts of work.For total flow, we show that the optimal flow corresponding to a particular energy budget cannot be exactly computed on a machine supporting arithmetic and the extraction of roots. This hardness result holds even when scheduling equal-work jobs on a uniprocessor. We do, however, extend previous work by Pruhs et al. to give an arbitrarilygood approximation for scheduling equal-work jobs on a multiprocessor.

References

  1. Advanced Micro Devices, Inc. AMD Athlon 64 processor power and thermal data sheet (ver. 3.43), Oct 2004. http://www.amd.com/us-en/assets/content_type/white_papers_and_tech_docs/30430.pdf.]]Google ScholarGoogle Scholar
  2. S. Albers and H. Fujiwara Energy-efficient algorithms for flow time minimization. In Proc. 23rd Intern. Symp. on Theoretical Aspects of Computer Science, pages 621--633, 2006.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. N. Alon, Y. Azar, G.J. Woeginger, and T. Yadid. Approximation schemes for scheduling. In Proc. 8th Annual ACM-SIAM Symp. Discrete Algorithms, pages 493--500, 1997.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. C. Bajaj. The algebraic degree of geometric optimization problems. Discrete Comput. Geom., 3:177--191, 1988.]]Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. N. Bansal, T. Kimbrel, and K. Pruhs. Dynamic speed scaling to manage energy and temperature. In Proc. 45th Symp. Found. Computer Science, pages 520--529, 2004.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. N. Bansal and K. Pruhs. Speed scaling to manage temperature. In Proc. 22nd Intern. Symp. on Theoretical Aspects of Computer Science, pages 460--471, 2005.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. D.M. Brooks, P. Bose, S.E. Schuster, H. Jacobson, P.N. Kudva, A. Buyuktosunoglu, J. D. Wellman, V. Zyuban, M. Gupta, and P.W. Cook. Power-aware microarchitecture: Design and modeling challenges for next-generation microprocessors. IEEE Micro, 20(6):26--44, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. C. Chekuri and M.A. Bender. An efficient approximation algorithm for minimizing makespan on uniformly related machines. Journal of Algorithms, 41:212--224, 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J. J. Chen, T. W. Kuo, and H. I Lu. Power-saving scheduling for weakly dynamic voltage scaling devices. In Proc. 9th Workshop on Algorithms and Data Structures, number 3608 in LNCS, pages 338--349, 2005.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. F.A. Chudak and D.B. Shmoys. Approximation algorithms for precedence-constrained scheduling problems on parallel machines that run at different speeds. In Proc. 8th Annual ACM-SIAM Symp. Discrete Algorithms, pages 581--590, 1997.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. D.S. Dummit and R.M. Foote. Abstract Algebra. Prentice-Hall, Inc., Englewood Cliffs, NJ, 1991.]]Google ScholarGoogle Scholar
  12. A. El Gamal, C. Nair, B. Prabhakar, E. Uysal-Biyikoglu, and S. Zahedi. Energy-efficient scheduling of packet transmissions over wireless networks. In Proc. IEEE Infocom, pages 1773--1782, 2002.]]Google ScholarGoogle ScholarCross RefCross Ref
  13. M.R. Garey and D.S. Johnson. Computers and intractability: A guide to the theory of NP-completeness. W.H. Freeman and Company, 1979.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Irani and K.R. Pruhs. Algorithmic problems in power management. SIGACT News, 32(2):63--76, 2005.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. T. Mudge. Power: A first-class architectural design constraint. Computer, 34(4):52--58, 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. M.L. Pinedo. Planning and scheduling in manufacturing and services. Springer Series in Operations Research. Springer Science+Business Media, Inc., 2005.]]Google ScholarGoogle Scholar
  17. K. Pruhs, P. Uthaisombut, and G. Woeginger. Getting the best response for your erg. In Proc. 9th Scandanavian Workshop on Algorithm Theory, volume 3111 of LNCS, pages 14--25, 2004.]]Google ScholarGoogle ScholarCross RefCross Ref
  18. K. Pruhs, R. van Stee, and P. Uthaisombut. Speed scaling of tasks with precedence constraints. In Proc. 3rd Workshop on Approximation and Online Algorithms, volume 3879 of LNCS, pages 307--319, 2005.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. The GAP Group. Gap system for computational discrete algebra. http://turnbull.mcs.st-and.ac.uk/~gap/.]]Google ScholarGoogle Scholar
  20. V. Tiwari, D. Singh, S. Rajgopal, G. Mehta, R. Patel, and F. Baez. Reducing power in high-performance microprocessors. In Proc. 35th ACM/IEEE Design Automation Conference, pages 732--737, 1998.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. E. Uysal-Biyikoglu, B. Prabhakar, and A. El Gamal. Energy-efficient packet transmission over a wireless link. IEEE/ACM Trans. Networking, 10(4):487--499, Aug. 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. M. Weiser, B. Welch, A. Demers, and S. Shenker. Scheduling for reduced cpu energy. In Proc. 1st Symp. on Operating Systems Design and Implementation, pages 13--23, 1994.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. F. Xie, M. Martonosi, and S. Malik. Compile-time dynamic voltage scaling settings: Opportunities and limits. In Proc. 2005 ACM SIGPLAN Conf. on Programming Language Design and Implementation, pages 49--62, 2003.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. F. Yao, A. Demers, and S. Shenker. A scheduling model for reduced CPU energy. In Proc. 36th Symp. Found. Computer Science, pages 374--382, 1995.]] Google ScholarGoogle ScholarDigital LibraryDigital Library

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            cover image ACM Conferences
            SPAA '06: Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
            July 2006
            344 pages
            ISBN:1595934529
            DOI:10.1145/1148109

            Copyright © 2006 ACM

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            • Published: 30 July 2006

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