Abstract
Thermal modeling and management techniques have been widely investigated in recent years. Prior studies show thermal management could increase energy efficiency of data centers. The thermal impacts of CPUs on data storage have been extensively studied; however, disk thermal models are still in their infancy. In our study, we aim at building thermal models that take into account both CPUs and disks. We propose an approach to developing thermal models to estimate a data node’s outlet temperature based on its CPU and disk activities. Integrating our thermal model into an energy consumption model, we can evaluate the total energy cost of a data center. We apply our models to study the impact of various thermal management strategies on energy efficiency.
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P. Thibodeau, “Data centers use 2 % of U.S. energy, below forecast,” 2011. [Online]. Available: http://blogs.computerworld.com/18738/data_centers_use_2_of_u_s_energy_below_forecast.
IDC, “Annual it spending by Western European utilities to reach 12.7 billion by 2017, says IDC energy insights,” 2013. [Online]. Available: http://www.idc-ei.com/getdoc.jsp?containerId=prUS24251013.
M. Baile, “The economics of virtualization: Moving toward an application-based cost mode,” 2009. [Online]. Available: http://www.vmware.com/files/pdf/Virtualization-application-based-cost-model-WP-EN.pdf.
J. He, “Datacenter power management: Power consumption trend,” 2008. [Online]. Available: http://communities.intel.com/community/datastack/blog/2008/02/20/datacenter-power-management-power-consumption-trend.
Statista, “Number of monthly active Facebook users worldwide from 3rd quarter 2008 to 2nd quarter 2013 (in millions),” 2013. [Online]. Available: http://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/.
“What happens on Facebook in each day?” 2012. [Online]. Available: http://visual.ly/what-happens-facebook-each-day.
“Whetstone,” http://www.netlib.org/benchmark/whetstones.
J. Katcher, “Postmark: A new file system benchmark,” System, no. 3022, pp. 1–8, 1997. [Online]. Available: http://www.netapp.com/tech_library/3022.html.
P. Jones, “Industry census 2012: Emerging data center markets,” 2012. [Online]. Available: http://www.datacenterdynamics.com/blogs/industry-census-2012-emerging-data-center-markets.
Y. Lee and A. Zomaya, “EnglishEnergy efficient utilization of resources in cloud computing systems,” EnglishThe Journal of Supercomputing, vol. 60, no. 2, pp. 268–280, 2012. [Online]. Available: http://dx.doi.org/10.1007/s11227-010-0421-3.
Z. Liu, Y. Chen, C. Bash, A. Wierman, D. Gmach, Z. Wang, M. Marwah, and C. Hyser, “Renewable and cooling aware workload management for sustainable data centers,” SIGMETRICS Perform. Eval. Rev., vol. 40, no. 1, pp. 175–186, Jun. 2012. [Online]. Available: http://doi.acm.org/10.1145/2318857.2254779.
M. AlAssaf, X. Jiang, M. Abid, and X. Qin, “EnglishEco-storage: A hybrid storage system with energy-efficient informed prefetching,” EnglishJournal of Signal Processing Systems, vol. 72, no. 3, pp. 165–180, 2013. [Online]. Available: http://dx.doi.org/10.1007/s11265-013-0784-9.
D. Colarelli and D. Grunwald, “Massive arrays of idle disks for storage archives,” in Proceedings of the 2002 ACM/IEEE conference on Supercomputing, ser. Supercomputing '02. Los Alamitos, CA, USA: IEEE Computer Society Press, 2002, pp. 1–11. [Online]. Available: http://dl.acm.org/citation.cfm?id=762761.762819.
E. Pinheiro and R. Bianchini, “Energy conservation techniques for disk array-based servers,” in Proceedings of the 18th annual international conference on Supercomputing, ser. ICS '04. New York, NY, USA: ACM, 2004, pp. 68–78. [Online]. Available: http://doi.acm.org/10.1145/1006209.1006220.
A. Beloglazov and R. Buyya, “Energy efficient resource management in virtualized cloud data centers,” in Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, ser. CCGRID '10. Washington, DC, USA: IEEE Computer Society, 2010, pp. 826–831. [Online]. Available: http://dx.doi.org/10.1109/CCGRID.2010.46
A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing,” Future Generation Computer Systems, vol. 28, no. 5, pp. 755–768, 2012, <ce:title>Special Section: Energy efficiency in large-scale distributed systems</ce:title>. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0167739X11000689.
B. Aksanli, J. Venkatesh, L. Zhang, and T. Rosing, “Utilizing green energy prediction to schedule mixed batch and service jobs in data centers,” SIGOPS Oper. Syst. Rev., vol. 45, no. 3, pp. 53–57, Jan. 2012. [Online]. Available: http://doi.acm.org/10.1145/2094091.2094105.
“7 strategies to optimize data centre cooling,” http://www.biztechmagazine.com/article/2011/01/keep-your-cool/.
J. Moore, J. Chase, P. Ranganathan, and R. Sharma, “Making scheduling “cool”: temperature-aware workload placement in data centers,” in Proceedings of the annual conference on USENIX Annual Technical Conference, ser. ATEC '05. Berkeley, CA, USA: USENIX Association, 2005, pp. 5–5. [Online]. Available: http://dl.acm.org/citation.cfm?id=1247360.1247365.
Q. Tang, S. Gupta, and G. Varsamopoulos, “Thermal-aware task scheduling for data centers through minimizing heat recirculation,” in Cluster Computing, 2007 IEEE International Conference on, sept. 2007, pp. 129–138.
Q. Tang, S. K. S. Gupta, and G. Varsamopoulos, “Energy-efficient thermal-aware task scheduling for homogeneous high-performance computing data centers: A cyber-physical approach,” IEEE Trans. Parallel Distrib. Syst., vol. 19, no. 11, pp. 1458–1472, Nov. 2008. [Online]. Available: http://dx.doi.org/10.1109/TPDS.2008.111.
K. Skadron, M. R. Stan, K. Sankaranarayanan, W. Huang, S. Velusamy, and D. Tarjan, “Temperature-aware microarchitecture: Modeling and implementation,” ACM Trans. Archit. Code Optim., vol. 1, no. 1, pp. 94–125, Mar. 2004. [Online]. Available: http://doi.acm.org/10.1145/980152.980157.
P. Eibeck and D. Cohen, “Modeling thermal characteristics of a fixed disk drive,” Components, Hybrids, and Manufacturing Technology, IEEE Transactions on, vol. 11, no. 4, pp. 566–570, dec 1988.
C. Tan, J. Yang, J. Mou, and E. Ong, “Three dimensional finite element model for transient temperature prediction in hard disk drive,” in Magnetic Recording Conference, 2009. APMRC '09. Asia-Pacific, jan. 2009, pp. 1–2.
S. Gurumurthi, A. Sivasubramaniam, and V. K. Natarajan, “Disk drive roadmap from the thermal perspective: A case for dynamic thermal management,” SIGARCH Comput. Archit. News, vol. 33, no. 2, pp. 38–49, May 2005. [Online]. Available: http://doi.acm.org/10.1145/1080695.1069975.
Y. Kim, S. Gurumurthi, and A. Sivasubramaniam, “Understanding the performance-temperature interactions in disk i/o of server workloads,” in High-Performance Computer Architecture, 2006. The Twelfth International Symposium on, feb. 2006, pp. 176–186.
X. Jiang, M. Alghamdi, J. Zhang, M. Assaf, X. Ruan, T. Muzaffar, and X. Qin, “Thermal modeling and analysis of storage systems,” in Performance Computing and Communications Conference (IPCCC), 2012 IEEE 31st International, 2012, pp. 31–40.
X. Jiang, M. AlAssaf, J. Zhang, M. Alghamdi, X. Ruan, T. Muzaffar, and X. Qin, “EnglishThermal modeling of hybrid storage clusters,” EnglishJournal of Signal Processing Systems, vol. 72, no. 3, pp. 181–196, 2013. [Online]. Available: http://dx.doi.org/10.1007/s11265-013-0787-6.
J. Lin, H. Zheng, Z. Zhu, and Z. Zhang, “Thermal modeling and management of dram systems,” IEEE Transactions on Computers, vol. 99, no. PrePrints, 2012.
A. Shah, V. Carey, C. Bash, C. Patel, and R. Sharma, “EnglishExergy analysis of data center thermal management systems,” in EnglishEnergy Efficient Thermal Management of Data Centers, Y. Joshi and P. Kumar, Eds. Springer US, 2012, pp. 383–446. [Online]. Available: http://dx.doi.org/10.1007/978-1-4419-7124-1_9.
R. Sharma, C. Bash, C. Patel, R. Friedrich, and J. Chase, “Balance of power: dynamic thermal management for internet data centers,” Internet Computing, IEEE, vol. 9, no. 1, pp. 42–49, jan.-feb. 2005.
O. Sarood, A. Gupta, and L. Kale, “Temperature aware load balancing for parallel applications: Preliminary work,” in Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on, may 2011, pp. 796–803.
O. Sarood and L. V. Kale, “A `cool' load balancer for parallel applications,” in Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, ser. SC '11. New York, NY, USA: ACM, 2011, pp. 21:1–21:11. [Online]. Available: http://doi.acm.org/10.1145/2063384.2063412.
J. Li, M. Qiu, J.-W. Niu, L. T. Yang, Y. Zhu, and Z. Ming, “Thermal-aware task scheduling in 3d chip multiprocessor with real-time constrained workloads,” ACM Trans. Embed. Comput. Syst., vol. 12, no. 2, pp. 24:1–24:22, Feb. 2013. [Online]. Available: http://doi.acm.org/10.1145/2423636.2423642.
J. Srinivasan and S. V. Adve, “Predictive dynamic thermal management for multimedia applications,” in Proceedings of the 17th annual international conference on Supercomputing, ser. ICS '03. New York, NY, USA: ACM, 2003, pp. 109–120. [Online]. Available: http://doi.acm.org/10.1145/782814.782831.
L. Ramos and R. Bianchini, “C-oracle: Predictive thermal management for data centers,” in High Performance Computer Architecture, 2008. HPCA 2008. IEEE 14th International Symposium on, feb. 2008, pp. 111–122.
X.-F. Jiang, J. Zhang, M. I. Alghamdi, X. Qin, M.-H. Jiang, and J.-F. Zhang, “Peam: Predictive energy-aware management for storage systems,” in Proceedings of 8th IEEE International Conference on Networking, Architecture, and Storage.
“Wd1600aajs specification,” http://www.wdc.com/wdproducts/library/SpecSheet/ENG/2879-701277.pdf.
“What happens on line in 60 seconds?” http://www.mediabistro.com/alltwitter/online-60-seconds_b46813.
“Dropbox statistics,” http://techcrunch.com/2012/11/13/dropbox-100-million/.
Acknowledgments
This research was supported by the U.S. National Science Foundation under Grants CCF-0845257 (CAREER), CNS-0917137 (CSR), CNS-0757778 (CSR), CCF-0742187 (CPA), CNS-0831502 (CyberTrust), CNS-0855251 (CRI), OCI-0753305 (CI-TEAM), DUE-0837341 (CCLI), and DUE-0830831 (SFS). Meikang Qiu’s research was support by NSF CNS-1359557 and NSFC 61071061.
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Jiang, X., Zhang, J., Qin, X., Qiu, M., Jiang, M., Zhang, J. (2015). Thermal Modeling and Management of Storage Systems in Data Centers. In: Khan, S., Zomaya, A. (eds) Handbook on Data Centers. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2092-1_30
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