Power Saving Analysis and Experiments for Large Scale Global Optimization

Simple item page
dc.contributor.authorCao, Zhenweien
dc.contributor.committeechairWatson, Layne T.en
dc.contributor.committeememberFeng, Wu-chunen
dc.contributor.committeememberCameron, Kirk W.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T20:41:15Zen
dc.date.adate2009-08-03en
dc.date.available2014-03-14T20:41:15Zen
dc.date.issued2009-07-06en
dc.date.rdate2009-08-03en
dc.date.sdate2009-07-09en
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
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-07092009-200715en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07092009-200715/en
dc.identifier.urihttp://hdl.handle.net/10919/33944en
dc.publisherVirginia Techen
dc.relation.haspartCaoThesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectVTDIRECT95en
dc.subjectpower aware computingen
dc.subjecthigh performance computingen
dc.subjectDVFSen
dc.subjectlarge scale global optimizationen
dc.subjectbudding yeast problemen
dc.titlePower Saving Analysis and Experiments for Large Scale Global Optimizationen
dc.typeThesisen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
CaoThesis.pdf
Size:
179.54 KB
Format:
Adobe Portable Document Format
Download

Collections

Masters Theses