|
|
Green challenges to system software in data centers |
Yuzhong SUN1( ), Yiqiang ZHAO1, Ying SONG1, Yajun YANG1,2, Haifeng FANG1,2, Hongyong ZANG1,2, Yaqiong LI1,2, Yunwei GAO1 |
1. Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China; 2. Graduate University of Chinese Academy of Sciences, Beijing 100190, China |
|
|
Abstract With the increasing demand and the wide application of high performance commodity multi-core processors, both the quantity and scale of data centers grow dramatically and they bring heavy energy consumption. Researchers and engineers have applied much effort to reducing hardware energy consumption, but software is the true consumer of power and another key in making better use of energy. System software is critical to better energy utilization, because it is not only the manager of hardware but also the bridge and platform between applications and hardware. In this paper, we summarize some trends that can affect the efficiency of data centers. Meanwhile, we investigate the causes of software inefficiency. Based on these studies, major technical challenges and corresponding possible solutions to attain green system software in programmability, scalability, efficiency and software architecture are discussed. Finally, some of our research progress on trusted energy efficient system software is briefly introduced.
|
Keywords
green software
multi-core
data center
power efficient system software
|
Corresponding Author(s):
SUN Yuzhong,Email:yuzhongsun@ict.ac.cn
|
Issue Date: 05 September 2011
|
|
1 |
Poess M, Nambiar R O. Energy cost, the key challenge of today's data centers: a power consumption analysis of TPC-C results. Proceedings of the VLDB Endowment , 2008, 1(2): 1229-1240
|
2 |
Wirth N. A plea for lean software. Computer , 1995, 28(2): 64-68 doi: 10.1109/2.348001
|
3 |
Owens J D, Luebke D, Govindaraju N, Harris M, Krüger J, Lefohn A E, Purcell T J. A survey of general-purpose computation on graphics hardware. In: Proceedings of 2005 Annual Conference of the European Association for Computer Graphics . 2005, 21-51
|
4 |
Foster I, Zhao Y, Raicu I, Lu S. Cloud computing and grid computing 360-degree compared. In: Proceedings of 2008 Grid Computing Environments Workshop . 2008, 1-10
|
5 |
Kogge P, Bergman K, Borkar S, Campbell D, Carlson W, Dally W, Denneau M, Franzon P, Harrod W, Hill K, Hiller J, Karp S, Keckler S, Klein D, Lucas R, Richards M, Scarpelli A, Scot S, Snavely A, Sterling T, Williams R S, Yelick K.Exascale computing study: technology challenges in achieving exascale systems. DARPA Report . 2008.
|
6 |
Moore G E. Progress in digital integrated electronics. In: Proceedings of IEEE Digital Integrated Electronic Device Meeting . 1975, 11-13
|
7 |
Kish L B. End of Moore’s law: thermal (noise) death of integration in micro and nano electronics. Physics Letters A , 2002, 305(3-4): 144-149 doi: 10.1016/S0375-9601(02)01365-8
|
8 |
Lloyd S. Ultimate physical limits to computation. Nature , 2000, 406(6799): 1047-1054 doi: 10.1038/35023282 pmid:10984064
|
9 |
Manferdelli J. Supercomputing and mass market desktops. ACM Super Computing , 2007
|
10 |
Seiler L, Carmean D, Sprangle E, Forsyth T, Abrash M, Dubey P, Junkins S, Lake A, Suqerman J, Cavin R, Espasa R, Grochowski E, Juan T, Hanrahan P. Larrabee: a many-core x86 architecture for visual computing. ACM Transactions on Graphics , 2008, 27(3): 1-15 doi: 10.1145/1360612.1360617
|
11 |
Geer D. Chip makers turn to multicore processors. Computer , 2005, 38(5): 11-13 doi: 10.1109/MC.2005.160
|
12 |
Environmental Protection Agency. EPA report to Congress on server and data center energy efficiency. 2007, http://www.energystar.gov/ia/partners/prod_development/downloads/EPA_Datacenter_Report_Congress_Final1.pdf
|
13 |
Brown D J, Reams C. Toward energy-efficient computing. Communications of the ACM , 2010, 53(3): 50-58 doi: 10.1145/1666420.1666438
|
14 |
Kant K. Data center evolution: a tutorial on state of the art, issues, and challenges. Computer Networks , 2009, 53(17): 2939-2965 doi: 10.1016/j.comnet.2009.10.004
|
15 |
Dally W J, Balfour J, Black-Shaffer D, Chen J, Harting R C, Parikh V, Park J, Sheffield D. Efficient embedded computing. Computer , 2008, 41(7): 27-32 doi: 10.1109/MC.2008.224
|
16 |
Chu S. The energy problem and Lawrence Berkeley National Laboratory. Talk given to the California Air Resources Board . 2008
|
17 |
Brown D, Furber S. A conversation with Steve Furber. ACM Queue: Tomorrow's Computing Today , 2010, 8(2): 1-8 doi: 10.1145/1716383.1716385
|
18 |
Saxe E. Power-efficient software. Communications of the ACM , 2010, 53(2): 44-48 doi: 10.1145/1646353.1646370
|
19 |
Chamberlain B L, Callahan D, Zima H P. Parallel programmability and the Chapel language. International Journal of High Performance Computing Applications , 2007, 21(3): 291-312 doi: 10.1177/1094342007078442
|
20 |
Dean J, Ghemawat S. MapReduce: simplified data processing on large clusters. Communications of the ACM , 2008, 51(1): 107-113 doi: 10.1145/1327452.1327492
|
21 |
Fatahalian K, Horn D R, Knight T J, Leem L, Houston M, Park J Y, Erez M, Ren M, Aiken A, Dally W J, Hanrahan P. Sequoia: programming the memory hierarchy. In: Proceedings of 2006 ACM/IEEE Conference on Supercomputing . 2006
|
22 |
Hoisie A, Getov V. Extreme-scale computing-where ‘just more of the same’ does not work. Computer , 2009, 42(11): 24-26 doi: 10.1109/MC.2009.354
|
23 |
Torrellas J. Architectures for extreme-scale computing. Computer , 2009, 42(11): 28-35 doi: 10.1109/MC.2009.341
|
24 |
Barker K J, Davis K, Hoisie A, Kerbyson D J, Lang M, Pakin S, Sancho J C. Using performance modeling to design large-scale systems. Computer , 2009, 42(11): 42-49 doi: 10.1109/MC.2009.372
|
25 |
Chase J S, Anderson D C, Thakar P N, Vahdat A M, Doyle R P. Managing energy and server resources in hosting centers. In: Proceedings of 18th ACM Symposium on Operating Systems Principles . 2001, 103-116
|
26 |
Zeng H, Ellis C S, Lebeck A R, Vahdat A. ECOSystem: managing energy as a first class operating system resource. In: Proceedings of 10th International Conference on Architectural Support for Programming Languages and Operating Systems . 2002, 123-132
|
27 |
Song Y, Zhang Y W, Sun Y Z, Shi W S. Utility analysis for internet-oriented server consolidation in VM-based data centers. In: Proceedings of 2009 IEEE International Conference on Cluster Computing . 2009, 1-10
|
28 |
Padala P, Hou K Y, Shin K G, Zhu X, Uysal M, Wang Z, Singhal S, Merchant A. Automated control of multiple virtualized resources. In: Proceedings of 4th ACM European conference on Computer systems . 2009, 13-26
|
29 |
Elnozahy M, Kistler M, Rajamony R. Energy conservation policies for web servers. In: Proceedings of the 4th USENIX Symposium on Internet Technologies and Systems . 2003, 99-112
|
30 |
Song Y, Wang H, Li Y Q, Feng B Q, Sun Y Z. Multi-tiered on-demand resource scheduling for VM-based data center. In: Proceedings of 9th IEEE/ACM International Symposium on Cluster Computing and the Grid . 2009, 148-155
|
31 |
Song Y, Li Y Q, Wang H, Zhang Y F, Feng B Q, Zang H Y, Sun Y Z. A service-oriented priority-based resource scheduling scheme for virtualized utility computing. In: Proceedings of 15th International Conference on High Performance Computing . 2008, 220-231
|
32 |
Padala P, Shin K, Zhu X, Uysal M, Wang Z, Singhal S, Merchant A, Salem K. Adaptive control of virtualized resources in utility computing environments. In: Proceedings of 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems . 2007, 289-302
|
33 |
Sun Y Z, Fang H F, Song Y, Du L, Zhang K, Zang H Y, Li Y Q, Yang Y J, Ao R, Huang Y B, Gao Y W. TRainbow: a new trusted virtual machine based platform. Frontiers of Computer Science in China , 2010, 4(1): 47-64 doi: 10.1007/s11704-009-0076-5
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|