On prediction to dynamically assign heterogeneous microprocessors to the minimum joint power state to achieve Ultra Low Power Cloud Computing

Conference Record - Asilomar Conference on Signals, Systems and Computers

Volumn , Issue , 2010, Pages 1269-1273

  Nagothu, Kranthimanoj ^a   Kelley, Brain ^a   Prevost, Jeff ^a   Jamshidi, Mo ^a  

^a UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

Author keywords

Adaptive algorithms; efficient cloud systems; optimal task allocation and ultra low power model

Indexed keywords

COMPUTING CENTER; COMPUTING SYSTEM; EFFICIENT CLOUD SYSTEMS; HETEROGENEOUS PROCESSORS; JOINT POWER; NOVEL CONCEPT; ON-DEMAND APPLICATIONS; OPTIMAL TASK ALLOCATION AND ULTRA- LOW POWER MODEL; PERFORMANCE CAPABILITY; POWER REDUCTIONS; SOFTWARE APPLICATIONS; TOTAL POWER; ULTRA LOW POWER;

ADAPTIVE ALGORITHMS; COMPUTER SYSTEMS;

CLOUD COMPUTING;

EID: 79958011967     PISSN: 10586393     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACSSC.2010.5757735     Document Type: Conference Paper

References (15)

1. http://msdn.microsoft.com/en- s/library/dd393312.aspx
2. J.G. Koomey, "Estimating Total Power Consumption byServers in the U.S. and the World"; http://enterprise.amd.com/
3. D. C. A. Jeffrey S. Chase, Prachi N. Thakar, Amin M. Vahdat and Ronald P. Doyle, "Managing Energy and Server Resources in Hosting Centers," in Eighteenth ACM symposium on Operating systems principles 2001.
4. M. Elnozahy, Kistler, Mike, Rajamony and Ram, "Energy-efficient server clusters," presented at the Second Workshop on Power Aware Computing Systems, Cambridge, 2002.
5. D. R. a. R. Gupta, "System Level Online Power Management Algorithms," presented at the Design, Automation and Test Europe, 2000.
6. M. Mani B. Srivastava, IEEE, Anantha P. Chandrakasan, and F. and Robert W. Brodersen, IEEE, "Predictive System Shutdown and Other Architectural Techniques for Energy Efficient Programmable Computation," IEEE Transactions on VLSI systems, vol. 4, p. 15, March 1996.
7. J. R. L. a. A. J. Smith, "Improving Dynamic Voltage Scaling Algorithms with PACE," in ACM SIGMETRICS, 2001.
8. S. R. K. Flautner, and T. Mudge, "Automatic performance setting for dynamic voltage scaling," in Mobile computing and networking,, 2001, pp. 260-271.
9. T. I. a. H. Yasuura, "Voltage Scheduling Problem for dynamically variable voltage processors," in IEEE International Symposium on Low Power Electronics and Design, 1998, pp. 197-202.
10. G. D. a. T. S. Rosing, "System-Level Power Management Using Online Learning," IEEE Transactions on CAD of integrated circuits and systems vol. 28, pp. 676-689, 2009.
11. C.-H. H. a. A.Wu, "A Predictive System Shutdown Method for Energy Saving of Event-Driven Computation," in International Conference on Computer Aided Design, 1997, pp. 28-32.
12. T.Simunic,Eds, "Dynamic Management of Power Consumption (Series In Computer Science. 2002, p.∧pp. Pages.
13. Monson Hayes, Statistical Signal Processing, John Wiley and Sons, 1996.
14. Byung-Gon Chun, Gianluca Iannaccone, Giuseppe Iannaccone, Randy katz, Gunho Lee and Luca Niccolini,"An Energy Case for Hybrid Datacenters", in Hot Power, 2009
15. Xiaoban Fan, Wolf-Dietrich Weber and Luiz André Barroso, "Power Provisioning for a Warehouse-Sized Computer", in ACM Int Symposium on Computer Architecture, 2007