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EnergySaving Cluster Roll: Power Saving System for Clusters ⋆ ManuelF.Dolz,JuanC.Fernández, Rafael Mayo, and Enrique S. Quintana-Ortí Depto. de Ingeniería y Ciencia de los Computadores, Universidad Jaime I, 12071-Castellón, Spain dolzm@guest.uji.es, {jfernand,mayo,quintana}@icc.uji.es Abstract. With the increasing number of nodes in high performance clusters as well as the high frequency of the processors in these systems, energy consumption has become a key factor which limits their largescale deployment. In response, this paper presents a software module that, taking into consideration past and future users’ requests, implements energy saving policies, powering on and shutting down the system nodes. This tool employs Roll for clusters with Rocks R○ as operating system and Sun R○ Grid Engine as queue system. Keywords: High performance computing, data centers, green computing, power consumption, queue system. 1 Introduction High Performance Computing (HPC) clusters have been widely adopted by companies and research institutions for their data processing centers because of their parallel performance, high scalability, and low acquisition cost. On the other hand, further deployment of HPC clusters is limited due to their high maintenance costs in terms of energy consumption, required both by the system hardware and the air cooling equipment. In particular, some large-scale data processing centers consume the same energy power as 40,000 homes, and studies by the U.S. Environmental Protection Agency show that, in 2007, the power consumption of data centers in the United States was around 70 billion KWatt-hour, representing 5,000 million euros and the emission of 50 million tonnes of CO2 [1]. Since the benefits of HPC clusters are clear, scientists and technicians are currently showing special interest in all types of solutions and ideas to minimize energy costs in data processing centers: Energy-awareness has spread among researchers from organizations like IEEE, which have analyzed HPC clusters, concluding that a significant part of the energy consumed by these systems is due to the interconnection of its components (switches, network cards, links, etc.); following this result, energy-aware algorithms have been developed which can disable ⋆ This research was supported by projects CICYT TIN2008-06570-C04 and FEDER, and P1-1B2009 of the Fundación Caixa-Castellón/Bancaixa and UJI. C. Müller-Schloer, W. Karl, and S. Yehia (Eds.): ARCS 2010, LNCS 5974, pp. 162–173, 2010. c○ Springer-Verlag Berlin Heidelberg 2010
EnergySaving Cluster Roll: Power Saving System for Clusters 163 idle interconnections in the cluster [2]. Microsoft inspects the problem from a different viewpoint and one solution proposed is to share highly efficient power supplies among several nodes of the system, achieving significant energy savings [3]. In this context a well-known energy management technique is DVFS (Dynamic Voltage and Frequency Scaling). DVFS entails reducing the system energy consumption by decreasing the CPU supply voltage and the clock frequency (CPU speed) simultaneously. This technique has a great impact on the development of work aimed at reducing consumption in this research context [4,5,6]. The authors in [7] present an energy-aware method in order to partition the workload and reduce energy consumption in multiprocessor systems with support for DVS. Freeh et al. [8] analyze the energy-time tradeoff of a wide range of applications using highperformance cluster nodes that have several power-performance states to lowering energy and power, so that the energy-time tradeoff can be dynamically adjusted. In [9], the authors use economic criteria and energy to dispatch jobs to a small set of active servers, while other servers are transitioned to a low energy state. Alternative strategies to limit power consumption and required cooling of HPC clusters are based on switching on and shutting down the nodes, according to the needs of the users’ applications. An algorithm that makes load balancing and unbalancing decisions by considering both the total load imposed on the cluster and the power and performance implications of turning nodes off is described in [10]. Several policies to combine dynamic voltage scaling and turning on or off nodes to reduce the aggregate power consumption of a server cluster during periods of reduced workload are presented in [11]. Rock-solid [12] and PowerSaving [13] are prototype examples of this strategy which provide little functionality or are still under development. This paper presents a new application which follows the same strategy, but with a much more complete functionality. In particular, our tool allows the definition of different conditions to activate and deactivate and nodes for a full adaption to the requirements of the system administrator and/or the end user. The tool has been designed and implemented as a module (Roll) for Rocks R○ [14] and employs the Sun R○ Grid Engine (SGE) [15]. A simulation of the module under real conditions shows that its use combined with a reasonable policy deliver considerable energy savings compared with a conventional cluster in which all nodes are permanently active. The article is organized as follows: Section 2 presents the hardware and software tools used in the development of the energy saving module, and Section 3 reviews its implementation. Section 4 evaluates the performance of the energy saving module, in terms of impact on the power consumption and execution time of the applications. Finally, Section 5 describes some future lines of work and summarizes the conclusions. 2 Basic Hardware and Software Tools The target hardware platform used in this work is an HPC cluster that employs the NPACI Rocks R○ Linux distribution as operating system, equipped with a front-end node that is responsible of the queue system and the new energy saving module (Roll).
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Keynote Table of Contents HyVM - Hy
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Abdullah, Tariq 174 Alima, Luc Onan
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