CHERUB: power consumption aware cluster resource management

Kiertscher, Simon; Zinke, Jörg; Schnor, Bettina

doi:10.1007/s10586-011-0176-5

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…This technique already has been applied to Load-Balancing clusters in [23]- [27] and in VMware vSphere 2 and Citrix XenServer 3 hypervisors. Recently various software tools implementing this technique in HPC clusters have also been developed [28]- [30]. However, we consider that these solutions feature important limitations constraining their practical application along with the degree of optimality of the results achieved in terms of energy savings.…”

Section: Introductionmentioning

confidence: 99%

A software tool to efficiently manage the energy consumption of HPC clusters

Cocaña-Fernández

Sánchez

Ranilla

2015

2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Today, High Performance Computing clusters (HPC) are an essential tool owing to they are an excellent platform for solving a wide range of problems through parallel and distributed applications. Nonetheless, HPC clusters consume large amounts of energy, which combined with notably increasing electricity prices are having an important economical impact, forcing owners to reduce operation costs. In this work we propose a software, named EECluster, to reduce the high energy consumption of HPC clusters. EECluster works with both OGE/SGE and PBS/TORQUE resource management systems and automatically tunes its decision-making mechanism based on a machine learning approach. The quality of the obtained results using this software are evaluated by means of experiments made using actual workloads from the Scientific Modelling Cluster at Oviedo University and the academic-cluster used by the Oviedo University for teaching high performance computing subjects.

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Section: Introductionmentioning

confidence: 99%