Abstract
We are now developing a new metric of data center power efficiency to fairly evaluate the contribution of each improvement for power efficiency. In order to develop it, we built a testbed of a data center and measured power consumption of each components and environmental variables in some detail, including the power consumption and temperature of each node, rack and air conditioning unit, as well as load on the CPU, Disk I/O and the network. In these measurements we found that there was a significant imbalance of CPU temperatures that caused an imbalance in the power consumption of fans. We clarified the relationship between CPU load and fan speed, and showed that scheduling or rearrangement of nodes could reduce the power consumption of fans. We reduced fan power consumption by a maximum of 62% and total power consumption by a maximum of 12% by changing the scheduling of five nodes, changing the nodes used from hot nodes to cool nodes.
Similar content being viewed by others
References
Belady, C.: Green grid data center power efficiency metrics: PUE and DCIE. White paper: Metrics & Measurements, http://www.thegreengrid.org (2007)
Anderson, D., et al.: A framework for data center energy productivity. White paper: Metrics & Measurements, http://www.thegreengrid.org (2008)
Green IT Promotion Council: Concept of new metrics for data center energy efficiency. http://www.greenit-pc.jp/e/topics/release/100316_e.html (2010)
Itoh, S., Kodama, Y., Shimizu, S., Sekiguchi, S., Nakamura, H., Mori, N.: Power consumption and efficiency of cooling in a Data Center. In: Energy Efficient Grids, Clouds and Clusters Workshop (E2GC2), Conjunction with the 11th ACM/IEEE Int. Conf. on Grid Computing (Grid 2010), pp. 305–312 (2010)
Intel Math Kernel Library: http://software.intel.com/en-us/intel-mkl/
SPEC: http://www.spec.org/
Kim, K.H., Buyya, R., Kim, J.: Power aware scheduling of bag-of-tasks applications with deadline constraints on DVS-enabled clusters. In: Proc. of the IEEE Int. Symp. on Cluster Computing and the Grid (CCGRlD 2007), pp. 541–548 (2007)
Steinder, M., Whalley, I., Hanson, J.E., Kephart, J.O.: Coordinated management of power usage and runtime performance. In: Proc. of the IEEE Network Operations and Management Symposium (NOMS 2008), pp. 387–394 (2008)
Orgerie, A.C., Lefevre, L., Gelas, J.P.: Demystifying energy consumption in grids and clouds. In: Green Computing (WIPGC) Workshop, Conjunction with the First Int. Green Computing Conf. (IGCC 2010), pp. 335–342 (2010). Work in Progress
Chase, J.S., Anderson, D.C., Thakar, P.N., Vahdat, A.M., Doyle, R.P.: Managing energy and server resources in hosting centers. In: Proc. of the 18th ACM Symp. on Operating Systems Principles (SOSP 2001), pp. 103–116 (2001)
Pinheiro, E., Bianchini, R., Carrera, E.V., Heath, T.: Load balancing and unbalancing for power and performance in cluster-based systems. In: Workshop on Compilers and Operating Systems for Low Power (COLP 01), Conjunction with the 10th Int. Conf. on Parallel Architectures and Compilation Techniques (PACT’01) (2001)
Ahmad, F., Vijaykumar, T.N.: Joint optimization of idle and cooling power in data centers while maintaining response time. In: Proc. of the 15th Int. Conf. on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2010), pp. 243–259 (2010)
NEDO (New Energy and Industrial Technology Development Organization): Outline of NEDO 2008–2009, 124–125 (2009). http://www.nedo.go.jp/kankobutsu/pamphlets/kouhou/2008gaiyo_e/
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kodama, Y., Itoh, S., Shimizu, T. et al. Imbalance of CPU temperatures in a blade system and its impact for power consumption of fans. Cluster Comput 16, 27–37 (2013). https://doi.org/10.1007/s10586-011-0174-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-011-0174-7