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ABSTRACT
Much research has been conducted on energy management for memory and disks. Most studies use control algorithms that dynamically transition devices to low power modes after they are idle for a certain threshold period of time. The control algorithms used in the past have two major limitations. First, they require painstaking, application-dependent manual tuning of their thresholds to achieve energy savings without significantly degrading performance. Second, they do not provide performance guarantees.This article addresses these two limitations for both memory and disks, making memory/disk energy-saving schemes practical enough to use in real systems. Specifically, we make four main contributions. (1) We propose a technique that provides a performance guarantee for control algorithms. We show that our method works well for all tested cases, even with previously proposed algorithms that are not performance-aware. (2) We propose a new control algorithm, Performance-Directed Dynamic (PD), that dynamically adjusts its thresholds periodically, based on available slack and recent workload characteristics. For memory, PD consumes the least energy when compared to previous hand-tuned algorithms combined with a performance guarantee. However, for disks, PD is too complex and its self-tuning is unable to beat previous hand-tuned algorithms. (3) To improve on PD, we propose a simpler, optimization-based, threshold-free control algorithm, Performance-Directed Static (PS). PS periodically assigns a static configuration by solving an optimization problem that incorporates information about the available slack and recent traffic variability to different chips/disks. We find that PS is the best or close to the best across all performance-guaranteed disk algorithms, including hand-tuned versions. (4) We also explore a hybrid scheme that combines PS and PD algorithms to further improve energy savings.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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1
|
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2
|
Burger, D., Austin, T. M., and Bennett, S. 1996. Evaluating future microprocessors: The simplescalar tool set. Tech. Rep. CS-TR-1996-1308, University of Wisconsin, Madison, WI.
|
| |
3
|
Alper Buyuktosunoglu , Stanley Schuster , David Brooks , Pradip Bose , Peter W. Cook , David H. Albonesi, An Adaptive Issue Queue for Reduced Power at High Performance, Proceedings of the First International Workshop on Power-Aware Computer Systems-Revised Papers, p.25-39, November 12, 2000
|
 |
4
|
|
| |
5
|
|
 |
6
|
|
| |
7
|
|
| |
8
|
|
| |
9
|
|
 |
10
|
|
| |
11
|
Ganger, G. R., Worthington, B. L., and Patt, Y. N. The DiskSim Simulation Environment---Version 2.0 Reference Manual.
|
| |
12
|
|
 |
13
|
|
| |
14
|
|
| |
15
|
Huang, H., Pillai, P., and Shin, K. G. 2003. Design and implementation of power-aware virtual memory. In USENIX. Annual Technical Conference. 57--70.
|
 |
16
|
|
 |
17
|
|
| |
18
|
|
| |
19
|
IBM. IBM Hard Disk Drive---Ultrastar 36Z15.
|
| |
20
|
Irani, S., Shukla, S., and Gupta, R. 2001. Competitive analysis of dynamic power management strategies for systems with multiple power saving states. Tech. rep. (Sept.) University of California, Irvine, School of Information and Computer Science, Irvine, CA.
|
 |
21
|
|
| |
22
|
Krishnan, P., Long, P. M., and Vitter., J. S. 1995. Adaptive disk spindown via optimal rent-to-buy in probabilistic environments. In the 12th International Conference on Machine Learning. 322--330.
|
 |
23
|
Alvin R. Lebeck , Xiaobo Fan , Heng Zeng , Carla Ellis, Power aware page allocation, Proceedings of the ninth international conference on Architectural support for programming languages and operating systems, p.105-116, November 2000, Cambridge, Massachusetts, United States
|
| |
24
|
Charles Lefurgy , Karthick Rajamani , Freeman Rawson , Wes Felter , Michael Kistler , Tom W. Keller, Energy Management for Commercial Servers, Computer, v.36 n.12, p.39-48, December 2003
[doi> 10.1109/MC.2003.1250880]
|
| |
25
|
Li, K., Kumpf, R., Horton, P., and Anderson, T. E. 1994. A quantitative analysis of disk drive power management in portable computers. In Proceedings of the Winter USENIX. 279--291.
|
| |
26
|
Peter S. Magnusson , Magnus Christensson , Jesper Eskilson , Daniel Forsgren , Gustav Hållberg , Johan Högberg , Fredrik Larsson , Andreas Moestedt , Bengt Werner, Simics: A Full System Simulation Platform, Computer, v.35 n.2, p.50-58, February 2002
[doi> 10.1109/2.982916]
|
| |
27
|
|
| |
28
|
Maximum Throughput, Inc. 2002. Power, heat, and sledgehammer. White paper. Available at http://www.max-t.com/downloads/whitepapers/SledgehammerPowerHeat20411.pdf.
|
| |
29
|
Moore, F. 2002. More power needed. Energy User News, Nov 25th.
|
 |
30
|
G. A. Paleologo , L. Benini , A. Bogliolo , G. De Micheli, Policy optimization for dynamic power management, Proceedings of the 35th annual conference on Design automation, p.182-187, June 15-19, 1998, San Francisco, California, United States
[doi> 10.1145/277044.277094]
|
 |
31
|
|
| |
32
|
Rambus. 1999. Rdram. Available at http://www.rambus.com.
|
| |
33
|
Ruemmler, C. and Wilkes, J. 1993. UNIX disk access patterns. In Proceedings of the Winter USENIX Conference. 405--420.
|
 |
34
|
|
| |
35
|
Storage Systems Division. 1999. Adaptive power management for mobile hard drives. IBM White Paper.
|
 |
36
|
|
| |
37
|
John Zedlewski , Sumeet Sobti , Nitin Garg , Fengzhou Zheng , Arvind Krishnamurthy , Randolph Wang, Modeling Hard-Disk Power Consumption, Proceedings of the 2nd USENIX Conference on File and Storage Technologies, March 31-31, 2003, San Francisco, CA
|
| |
38
|
Lixin Zhang , Zhen Fang , Mide Parker , Binu K. Mathew , Lambert Schaelicke , John B. Carter , Wilson C. Hsieh , Sally A. McKee, The Impulse Memory Controller, IEEE Transactions on Computers, v.50 n.11, p.1117-1132, November 2001
[doi> 10.1109/12.966490]
|
| |
39
|
Qingbo Zhu , Francis M. David , Christo F. Devaraj , Zhenmin Li , Yuanyuan Zhou , Pei Cao, Reducing Energy Consumption of Disk Storage Using Power-Aware Cache Management, Proceedings of the 10th International Symposium on High Performance Computer Architecture, p.118, February 14-18, 2004
[doi> 10.1109/HPCA.2004.10022]
|
 |
40
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REVIEW
"Michael Zastre : Reviewer"
Anyone who has used devices with several energy-saving modes is aware of the latencies introduced, such as disk drives that take some time to spin up, or programs that become unexpectedly sluggish as memory chips take a break from their naps. High
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