Non-clairvoyant speed scaling for batched parallel jobs on multiprocessors

Proceedings of the 6th ACM Conference on Computing Frontiers, CF 2009

Volumn , Issue , 2009, Pages 99-107

  Sun, Hongyang ^a   Cao, Yangjie ^b   Hsu, Wen Jing ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Batched parallel jobs; Energy consumption; Flow time; Multiprocessors; Non clairvoyant; Power Budget; Scheduling; Simulations; Speed scaling

Indexed keywords

FLOW-TIME; MULTIPROCESSORS; NON-CLAIRVOYANT; PARALLEL JOBS; POWER BUDGETS; SIMULATIONS; SPEED SCALING;

ALGORITHMS; ENERGY UTILIZATION; PARALLEL PROCESSING SYSTEMS; SCHEDULING;

SPEED;

EID: 79953805933     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1531743.1531760     Document Type: Conference Paper

References (32)

1. S. Albers and H. Fujiwara. Energy-efficient algorithms for flow time minimization. ACM Transaction on Algorithms, 3(4):49, 2007.
2. S. Albers, F. Müller, and S. Schmelzer. Speed scaling on parallel processors. In SPAA, pages 289-298, San Diego, CA, USA, 2007.
3. N. Bansal, H. L. Chan, T. W. Lam, and L. K. Lee. Scheduling for speed bounded processors. In ICALP, pages 409-420, Reykjavik, Iceland, 2008.
4. N. Bansal, T. Kimbrel, and K. Pruhs. Dynamic speed scaling to manage energy and temperature. In FOCS, pages 520-529, Rome, Italy, 2004.
5. N. Bansal, K. Pruhs, and C. Stein. Speed scaling for weighted flow time. In SODA, pages 805-813, New Orleans, LA, USA, 2007.
6. M. A. Bender and M. O. Rabin. Scheduling Cilk multithreaded computations on processors of different speeds. In SPAA, pages 13-21, Bar Harbor, ME, USA, 2000.
7. A. Borodin and R. El-Yaniv. Online computation and competitive analysis. Cambridge University Press, New York, NY, USA, 1998.
8. 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.
9. D. P. Bunde. Power-aware scheduling for makespan and flow. In SPAA, pages 190-196, Cambridge, MA, USA, 2006.
10. H.-L. Chan, J. Edmonds, T.-W. Lam, L.-K. Lee, A. Marchetti-Spaccamela, and K. Pruhs. Nonclairvoyant speed scaling for flow and energy. In STACS, pages 409-420, Freiburg, Germany, 2009.
11. J.-J. Chen. Multiprocessor energy-efficient scheduling for real-time tasks with different power characteristics. In ICPP, pages 13-20, Oslo, Norway, 2005.
12. Z.-L. Chen. Simultaneous job scheduling and resource allocation on parallel machines. Annals of Operations Research, 129:135-153, 2004.
13. X. Deng, N. Gu, T. Brecht, and K. Lu. Preemptive scheduling of parallel jobs on multiprocessors. In SODA, pages 159-167, Philadelphia, PA, USA, 1996.
14. A. B. Downey. A parallel workload model and its implications for processor allocation. In HPDC, page 112, Portland, OR, USA, 1997.
15. J. Edmonds. Scheduling in the dark. In STOC, pages 179-188, Atlanta, GA, USA, 1999.
16. J. Edmonds, D. D. Chinn, T. Brecht, and X. Deng. Non-clairvoyant multiprocessor scheduling of jobs with changing execution characteristics. In STOC, pages 120-129, El Paso, TX, USA, 1997.
17. D. Grunwald, I. Charles B. Morrey, P. Levis, M. Neufeld, and K. I. Farkas. Policies for dynamic clock scheduling. In OSDI, pages 6-6, San Diego, CA, USA, 2000.
18. Y. He, W.-J. Hsu, and C. E. Leiserson. Provably efficient two-level adaptive scheduling. In JSSPP, Saint-Malo, France, 2006.
19. S. Irani and K. Pruhs. Algorithmic problems in power management. SIGACT News, 36(2):63-76, 2005.
20. C. Isci, A. Buyuktosunoglu, C.-Y. Cher, P. Bose, and M. Martonosi. An analysis of efficient multi-core global power management policies: Maximizing performance for a given power budget. In IEEE/ACM International Symposium on Microarchitecture, pages 347-358, Orlando, FL, USA, 2006.
21. J. M. Jaffe. An analysis of preemptive multiprocessor job scheduling. Mathematics of Operations Research, 5(3):415-421, 1980.
22. W. Kim, M. S. Gupta, G.-Y. Wei, and D. Brooks. System level analysis of fast, per-core DVFS using on-chip switching regulators. In HPCA, pages 123-134, Salt Lake City, UT, USA, 2008.
23. T.-W. Lam, L.-K. Lee, I. K. K. To, and P. W. H. Wong. Competitive non-migratory scheduling for flow time and energy. In SPAA, pages 256-264, Munich, Germany, 2008.
24. T. W. Lam, L.-K. Lee, I. K.-K. To, and P. W. H. Wong. Speed scaling functions for flow time scheduling based on active job count. In ESA, pages 647-659, Karlsruhe, Germany, 2008.
25. K. Pruhs. Competitive online scheduling for server systems. ACM SIGMETRICS Performance Evaluation Review, 34(4):52-58, 2007.
26. K. Pruhs, E. Torong, and J. Sgall. Online scheduling. In handbook of scheduling: Algorithms, models, and performance analysis, chapter 15, CRC Press. 2004.
27. K. Pruhs, P. Uthaisombut, and G. Woeginger. Getting the best response for your erg. ACM Transactions on Algorithms, 4(3):1-17, 2008.
28. K. Pruhs, R. van Stee, and P. Uthaisombut. Speed scaling of tasks with precedence constraints. In WAOA, pages 307-319, Mallorca, Spain, 2005.
29. H. Sebastian and M. Diana. Analysis of dynamic voltage/frequency scaling in chip-multiprocessors. In ISLPED, pages 38-43, Portland, OR, USA, 2007.
30. D. B. Shmoys and Eva Tardos. Scheduling unrelated machines with costs. In SODA, pages 448-454, Austin, Texas, USA, 1993.
31. J. Turek, U. Schwiegelshohn, J. L. Wolf, and P. S. Yu. Scheduling parallel tasks to minimize average response time. In SODA, pages 112-121, Philadelphia, PA, USA, 1994.
32. F. Yao, A. Demers, and S. Shenker. A scheduling model for reduced CPU energy. In FOCS, page 374, Milwaukee, WI, USA, 1995.