DocumentCode
262561
Title
Towards Generalizing "Big Little" for Energy Proportional HPC and Cloud Infrastructures
Author
Villebonnet, Violaine ; Da Costa, Georges ; Lefevre, Laurent ; Pierson, Jean-Marc ; Stolf, Patricia
Author_Institution
IRIT, Univ. of Toulouse, Toulouse, France
fYear
2014
fDate
3-5 Dec. 2014
Firstpage
703
Lastpage
710
Abstract
Reducing energy consumption is part of the main concerns in cloud and HPC environments. Today servers energy consumption is far from ideal, mostly because it remains very high even with low usage state. An energy consumption proportional to the server load would bring important savings in terms of electricity consumption and then financial costs for a data enter infrastructure. In this paper, we propose a platform composed of heterogeneous architectures to achieve proportional computing goal. We select low power ARM processor for a light load, and a range of regular x86 servers when performance is required. We propose a comparative study of benchmark execution in order to find the best configuration depending on the current load and show the effective results in terms of energy proportionality.
Keywords
cloud computing; computer centres; parallel processing; power aware computing; virtualisation; benchmark execution; big.LITTLE; cloud infrastructures; current load; datacenter infrastructure; electricity consumption; energy consumption reduction; energy proportional HPC; financial costs; heterogeneous architectures; low-power ARM processor; proportional computing; server energy consumption; server load; Computer architecture; Emulation; Hardware; Power demand; Servers; Virtual machining; Virtualization; ARM processor; emulation; energy proportionality; heterogeneous architectures; virtualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location
Sydney, NSW
Type
conf
DOI
10.1109/BDCloud.2014.99
Filename
7034863
Link To Document