Abstract
Energy has become a scarce and expensive resource. There is a growing awareness in society that energy saving is a critical issue. This paper surveys algorithmic solutions to reduce energy consumption in computing environments. We focus on the system and device level. More specifically, we study power-down mechanisms as well as dynamic speed scaling techniques in modern microprocessors.
An extended and modified version of this survey, aiming at a different audience, will appear in the Communications of the ACM.
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References
http://www.microsoft.com/whdc/system/pnppwr/powermgmt/default.mspx
Albers, S., Fujiwara, H.: Energy-efficient algorithms for flow time minimization. ACM Transactions on Algorithms 3 (2007)
Albers, S., Müller, F., Schmelzer, S.: Speed scaling on parallel processors. In: Proc. 19th ACM Symposium on Parallelism in Algorithms and Architectures, pp. 289–298 (2007)
Augustine, J., Irani, S., Swamy, C.: Optimal power-down strategies. SIAM Journal on Computing 37, 1499–1516 (2008)
Bansal, N., Bunde, D.P., Chan, H.-L., Pruhs, K.: Average rate speed scaling. In: Laber, E.S., Bornstein, C., Nogueira, L.T., Faria, L. (eds.) LATIN 2008. LNCS, vol. 4957, pp. 240–251. Springer, Heidelberg (2008)
Bansal, N., Chan, H.-L., Lam, T.-W., Lee, L.-K.: Scheduling for speed bounded processors. In: Aceto, L., Damgård, I., Goldberg, L.A., Halldórsson, M.M., Ingólfsdóttir, A., Walukiewicz, I. (eds.) ICALP 2008, Part I. LNCS, vol. 5125, pp. 409–420. Springer, Heidelberg (2008)
Bansal, N., Chan, H.-L., Pruhs, K.: Speed scaling with an arbitrary power function. In: Proc. 20th ACM-SIAM Symposium on Discrete Algorithm, pp. 693–701 (2009)
Bansal, N., Kimbrel, T., Pruhs, K.: Speed scaling to manage energy and temperature. Journal of the ACMÂ 54 (2007)
Bansal, N., Pruhs, K., Stein, C.: Speed scaling for weighted flow time. In: Proc. 18th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 805–813 (2007)
Baptiste, P., Chrobak, M., Dürr, C.: Polynomial time algorithms for minimum energy scheduling. In: Arge, L., Hoffmann, M., Welzl, E. (eds.) ESA 2007. LNCS, vol. 4698, pp. 136–150. Springer, Heidelberg (2007)
Barroso, L.A.: The price of performance. ACM Queue 3 (2005)
Bunde, D.P.: Power-aware scheduling for makespan and flow. In: Proc. 18th Annual ACM Symposiun on Parallel Algorithms and Architectures, pp. 190–196 (2006)
Chan, H.-L., Chan, W.-T., Lam, T.-W., Lee, K.-L., Mak, K.-S., Wong, P.W.H.: Energy efficient online deadline scheduling. In: Proc. 18th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 795–804 (2007)
Chan, H.-L., Edmonds, J., Lam, T.-W., Lee, L.-K., Marchetti-Spaccamela, A., Pruhs, K.: Nonclairvoyant speed scaling for flow and energy. In: Proc. 26th International Symposium on Theoretical Aspects of Computer Science, pp. 255–264 (2009)
Demaine, E.D., Ghodsi, M., Hajiaghayi, M.T., Sayedi-Roshkhar, A.S., Zadimoghaddam, M.: Scheduling to minimize gaps and power consumption. In: Proc. 19th Annual ACM Symposium on Parallel Algorithms and Architectures, pp. 46–54 (2007)
Irani, S., Karlin, A.R.: Online computation. In: Hochbaum, D. (ed.) Approximation Algorithms for NP-Hard Problems, pp. 521–564. PWS Publishing Company (1997)
Irani, S., Shukla, S.K., Gupta, R.K.: Online strategies for dynamic power management in systems with multiple power-saving states. ACM Transaction in Embedded Computing Systems 2, 325–346 (2003)
Irani, S., Pruhs, K.: Algorithmic problems in power management. SIGACT News 36, 63–76 (2005)
Irani, S., Shukla, S.K., Gupta, R.: Algorithms for power savings. ACM Transactions on Algorithms 3 (2007)
Karlin, A.R., Manasse, M.S., McGeoch, L.A., Owicki, S.S.: Competitive randomized algorithms for nonuniform problems. Algorithmica 11, 542–571 (1994)
Lam, T.-W., Lee, L.-K., To, I.K.K., Wong, P.W.H.: Energy efficient deadline scheduling in two processor systems. In: Tokuyama, T. (ed.) ISAAC 2007. LNCS, vol. 4835, pp. 476–487. Springer, Heidelberg (2007)
Lam, T.-W., Lee, L.-K., To, I.K.-K., Wong, P.W.H.: Competitive non-migratory scheduling for flow time and energy. In: Proc. 20th Annual ACM Symposium on Parallel Algorithms and Architectures, pp. 256–264 (2008)
Lam, T.-W., Lee, L.-K., To, I.K.K., Wong, P.W.H.: Speed scaling functions for flow time scheduling based on active job count. In: Halperin, D., Mehlhorn, K. (eds.) ESA 2008. LNCS, vol. 5193, pp. 647–659. Springer, Heidelberg (2008)
Li, M., Liu, B.J., Yao, F.F.: Min-energy voltage allocation for tree-structured tasks. Journal on Combintorial Optimization 11, 305–319 (2006)
Li, M., Yao, A.C., Yao, F.F.: Discrete and continuous min-energy schedules for variable voltage processors. Proc. National Academy of Sciences USA 103, 3983–3987 (2006)
Li, M., Yao, F.F.: An efficient algorithm for computing optimal discrete voltage schedules. SIAM Journal on Computing 35, 658–671 (2005)
Pruhs, K., Uthaisombut, P., Woeginger, G.J.: Getting the best response for your erg. ACM Transactions on Algorithms 4 (2008)
Pruhs, K., van Stee, R., Uthaisombut, P.: Speed scaling of tasks with precedence constraints. Theory of Computing Systems 43, 67–80 (2008)
Sleator, D.D., Tarjan, R.E.: Amortized efficiency of list update and paging rules. Communcations of the ACM 28, 202–208 (1985)
Yao, F.F., Demers, A.J., Shenker, S.: A scheduling model for reduced CPU energy. In: Proc. 36th IEEE Symposium on Foundations of Computer Science, pp. 374–382 (1995)
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Albers, S. (2009). Algorithms for Energy Saving. In: Albers, S., Alt, H., Näher, S. (eds) Efficient Algorithms. Lecture Notes in Computer Science, vol 5760. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03456-5_12
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DOI: https://doi.org/10.1007/978-3-642-03456-5_12
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