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dc.contributor.authorCao, Zhenweien_US
dc.date.accessioned2009-08-03en_US
dc.date.accessioned2014-03-14T20:41:15Z
dc.date.available2009-08-03en_US
dc.date.available2014-03-14T20:41:15Z
dc.date.issued2009-07-06en_US
dc.date.submitted2009-07-09en_US
dc.identifier.otheretd-07092009-200715en_US
dc.identifier.urihttp://hdl.handle.net/10919/33944
dc.description.abstractGreen computing, an emerging field of research that seeks to reduce excess power consumption in high performance computing (HPC), is gaining popularity among researchers. Research in this field often relies on simulation or only uses a small cluster, typically 8 or 16 nodes, because of the lack of hardware support. In contrast, System G at Virginia Tech is a 2592 processor supercomputer equipped with power aware components suitable for large scale green computing research. DIRECT is a deterministic global optimization algorithm, implemented in the mathematical software package VTDIRECT95. This thesis explores the potential energy savings for the parallel implementation of DIRECT, called pVTdirect, when used with a large scale computational biology application, parameter estimation for a budding yeast cell cycle model, on System G. Two power aware approaches for pVTdirect are developed and compared against the CPUSPEED power saving system tool. The results show that knowledge of the parallel workload of the underlying application is beneficial for power management.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartCaoThesis.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectVTDIRECT95en_US
dc.subjectpower aware computingen_US
dc.subjecthigh performance computingen_US
dc.subjectDVFSen_US
dc.subjectlarge scale global optimizationen_US
dc.subjectbudding yeast problemen_US
dc.titlePower Saving Analysis and Experiments for Large Scale Global Optimizationen_US
dc.typethesisen_US
dc.contributor.departmentComputer Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
dc.contributor.committeechairWatson, Layne T.en_US
dc.contributor.committeememberFeng, Wu-Chunen_US
dc.contributor.committeememberCameron, Kirk W.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07092009-200715/en_US


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