A Novel Method for Optimising Energy Efficiency in High-Performance Computing Systems
Abstract views: 57 / PDF downloads: 48
DOI:
https://doi.org/10.31039/plic.2024.11.248Keywords:
DVFS (Dynamic Voltage and Frequency Scaling), Server Virtualizations, High-Performance Computing (HPC) systems, Energy EfficiencyAbstract
This paper introduces a new method to promote energy efficiency in computing systems. The rapidly growing demand for computational power in high-performance computing (HPC) systems is accompanied by a significant increase in energy consumption. This research investigates the many ways to minimise energy consumption in HPC systems without sacrificing computational performance. Building upon previous research we combined and refined ideas to develop an optimised approach. Our method utilises a tri-modular framework incorporating an Energy-Efficient Hardware Design, Resource Management, and Optimisation, and Server Virtualisation. The first module employs a method of designing smart energy-efficient hardware. This method incorporates leakage reduction techniques such as clock gating and sleep states. The second module uses a technique focused on optimising server software. This method is based on Dynamic Voltage and frequency scaling (DVFS) for power management in data centres. The third module is based on server virtualisation and employs software to create multiple virtual machines on a single physical server allowing for a significant reduction in energy and hardware costs. The methods used in these three modules are systematically integrated to produce a more efficient consumption of electricity. This will allow for the computing system to minimise energy consumption without compromising computational power.
References
Ratković, I., Bežanić, N., Ünsal, O. S., Cristal, A., & Milutinović, V. (2015). An Overview of Architecture-Level Power- and Energy-Efficient Design Techniques. In Advances in computers (pp. 1–57). https://doi.org/10.1016/bs.adcom.2015.04.001
Beloglazov, A., Buyya, R., Lee, Y. C., & Zomaya, A. (2011). A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems. In Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computer Science and Software Engineering, the University of Melbourne, Melbourne, VIC 3010, Australia (Vol. 82, pp. 47–108). https://doi.org/10.1016/B978-0-12-385512-1.00003-7
Shao, Z., Iyer, V. S., & Xie, Y. (2010, April). DVFS-based dynamic thermal management for multi-core processors. In 2010 Design, Automation and Test in Europe Conference & Exhibition (DATE) (pp. 1617-1622). IEEE
Data centres & networks - IEA. (n.d.). IEA. https://www.iea.org/energy-system/buildings/data-centres-and-data-transmission-networs
Lin, C.-T., Huang, Y.-M., & Wen, Y.-C. (2016). Server consolidation techniques in virtualized data centers: A survey. The Journal of Supercomputing, 72(1), 105-12
Barham, P., Dragunov, B., Harris, E., Kay, R., & Newell, A. (2004). Xen: A virtual machine management system for x86-based PCs. ACM SIGOPS Operating Systems Review, 38(5), 186-199.
Monteclaro, A. J. (2023, November 20). Data Center Power Consumption: What You Need to Know.ServerWatch.https://www.serverwatch.com/virtualization/data-center-power-consumption/
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Aarah Sardesai, Saif Al Dulaimi, Merve Gokgol
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
Share: copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution-NonCommercial-NoDerivatives-No additional restrictions.
Authors retain copyright and agree to license their articles with a Creative Commons Attribution-NonCommercial-