By Topic

Intelligent Power Management Over Large Clusters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

8 Author(s)
A. Stephen McGough ; Newcastle Univ., Newcastle upon Tyne, UK ; Clive Gerrard ; Paul Haldane ; Dave Sharples
more authors

There is a growing tension within large organisations such as universities between the desire to perform vast amounts of computational processing and the desire to reduce power consumption by switching off computers. This situation will only worsen as computational problems get larger and the desire to save energy escalates. Through careful management of computing resources it is possible to maximise effective computer usage whilst minimising power consumption though this can be costly in terms of human effort. We present our work with the Agility Cloud Computing Platform to provide intelligent control over a University-wide Condor system, which works to reduce power consumption without adversely affecting the Condor users. This system also provides auditing of the power usage, which can be used to determine the power efficiency of the Condor system.

Published in:

Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom)

Date of Conference:

18-20 Dec. 2010