Abstract
The steady rise in energy consumption by data centers world wide over the last decade and the future 20 MW exascale-challenge in High Performance Computing (HPC) makes saving energy an important consideration for HPC data centers. A move from air-cooled HPC systems to indirect or direct water-cooled systems allowed for the use of chiller-less cold or hot water cooling. However, controlling such systems needs special attention in order to arrive at an optimal compromise of low energy consumption and robust operating conditions. This paper highlights a newly developed concept along with software tools for modeling the data center cooling circuits, collecting data, and simulating and analyzing operating conditions. A first model for the chiller-less cooling loop of the Leibniz Supercomputing Center (LRZ) will be presented and lessons learned will be discussed, demonstrating the possibilities offered by the new concept and tools.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Azevedo, D., French, D.A., Power, E.N.: \(\text{ Pue }^{{\rm TM}}\): a comprehensive examination of the metric. White paper 49 (2012)
Cassirer, K., Clees, T., Klaassen, B., Nikitin, I., Nikitina, L.: MYNTS User’s Manual, Release 3.3. Fraunhofer SCAI, Sankt Augustin (2015). www.scai.fraunhofer.de/mynts
Clees, T., Hornung, N., Nikitin, I., Nikitina, L., Steffes-lai, D.: DesParO User’s Manual, Release 2.4. Fraunhofer SCAI, Sankt Augustin, Germany, December 2014. www.scai.fraunhofer.de/desparo
DCD Intelligence: Is the industry getting better at using power? Data Center Dynamics FOCUS 33, January/February 2014 33, 16–17 (2014). http://content.yudu.com/Library/A2nvau/FocusVolume3issue33/resources/index.htm?referrerUrl=
Grundel, S., Hornung, N., Klaassen, B., Benner, P., Clees, T.: Computing surrogates for gas network simulation using model order reduction. In: Koziel, S., Leifsson, L. (eds.) Surrogate-Based Modeling and Optimization: Applications in Engineering. Springer, New York (2013)
Hackenberg, D., Schöne, R., Ilsche, T., Molka, D., Schuchart, J., Geyer, R.: An energy efficiency feature survey of the intel haswell processor (2015)
Leibniz Supercomputing Centre. http://www.lrz.de
Johnsson, L., Netzer, G.: SNIC/KTH; Eric Boyer, CINES; Paul Carpenter, BSC; Radosław Januszewski, PSNC; Giannis Koutsou, CaSToRC; Ole Widar Saastad, SIGMA/UiO; Giannos Stylianou, CaSToRC; Torsten Wilde, LRZ : D9.3.4 Final Report on Prototype Evaluation. PRACE 1IP-WP9 public deliverable p. 44 (2013). http://www.prace-ri.eu/IMG/pdf/d9.3.4_1ip.pdf
Rhein, B., Clees, T., Ruschitzka, M.: Robustness measures and numerical approximation of the cumulative density function of response surfaces. Comm. Statistics - Sim. Comp. 43(1), 1–17 (2014)
Shoukourian, H., Wilde, T., Auweter, A., Bode, A.: Monitoring power data: a first step towards a unified energy efficiency evaluation toolset for HPC data centers. Environ. Model. Softw. 56, 13–26 (2014). http://www.sciencedirect.com/science/article/pii/S1364815213002934, thematic issue on Modelling and evaluating the sustainability of smart solutions
Shoukourian, H., Wilde, T., Auweter, A., Bode, A.: Predicting the energy and power consumption of strong and weak scaling HPC applications. Supercomputing Frontiers and Innovations 1(2), 20–41 (2014)
SIMOPEK. http://www.simopek.de
SorTech AG. http://www.sortech.de/en/
Stansberry, M.: 2013 uptime institute annual data center industry survey report and full results. http://www.data-central.org/resource/collection/BC649AE0-4223-4EDE-92C7-29A659EF0900/uptime-institute-2013-data-center-survey.pdf
Top500 List. http://www.top500.org/
What is adsoprtion cooling? http://www.sortech.de/en/technology/adsorption/
Wilde, T., Auweter, A., Patterson, M., Shoukourian, H., Huber, H., Bode, A., Labrenz, D., Cavazzoni, C.: DWPE, a new data center energy-efficiency metric bridging the gap between infrastructure and workload. In: 2014 International Conference on High Performance Computing Simulation (HPCS), pp. 893–901, July 2014
Wilde, T., Auweter, A., Shoukourian, H.: The 4 Pillar Framework for energy efficient HPC data centers. In: Computer Science - Research and Development, pp. 1–11 (2013). http://dx.doi.org/10.1007/s00450-013-0244-6
Acknowledgments
The authors would like to thank Jeanette Wilde (LRZ) for her valuable comments and support.
The work presented here has been carried out within the SIMOPEK project [13], which has received funding from the German Federal Ministry for Education and Research under grant number 01IH13007A, at the Leibniz Supercomputing Centre (LRZ) with support of the State of Bavaria, Germany, and the Gauss Centre for Supercomputing (GCS).
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Wilde, T. et al. (2015). Increasing Data Center Energy Efficiency via Simulation and Optimization of Cooling Circuits - A Practical Approach. In: Gottwalt, S., König, L., Schmeck, H. (eds) Energy Informatics. EI 2015. Lecture Notes in Computer Science(), vol 9424. Springer, Cham. https://doi.org/10.1007/978-3-319-25876-8_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-25876-8_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25875-1
Online ISBN: 978-3-319-25876-8
eBook Packages: Computer ScienceComputer Science (R0)