Understanding the Impact of Hybrid Programming on Software Energy Efficiency

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dc.contributor.advisorZong, Ziliang
dc.contributor.advisorJin, Tongdan
dc.contributor.authorLaKomski, Donna
dc.contributor.committeeMemberBurtscher, Martin
dc.date.accessioned2016-08-23T16:11:32Z
dc.date.available2016-08-23T16:11:32Z
dc.date.issued2016-07
dc.description.abstractHigh performance computing systems today are heterogeneous in nature with multiple CPUs and accelerators/coprocessors in each computing node. The majority of today's programs only utilize single computing components (e.g. a CPU, GPU or Xeon Phi) while leaving other components idle (e.g. waiting for the results to be calculated). This may not be optimal for either performance or energy efficiency. Hybrid computing can solve this problem. Employing multiple device types can create more computing power on the platform, but can also create unexpected and unintended issues and challenges due to potential complex interactions of software and hardware. This thesis investigates the impact of hybrid computing on the performance and energy-efficiency of parallel applications, provides a guideline for hybrid work division, and develops a model to predict optimal performance or energy-efficiency.
dc.description.departmentComputer Science
dc.formatText
dc.format.extent90 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationLaKomski, D. (2016). <i>Understanding the impact of hybrid programming on software energy efficiency</i> (Unpublished thesis). Texas State University, San Marcos, Texas.
dc.identifier.urihttps://hdl.handle.net/10877/6261
dc.language.isoen
dc.subjectParallel
dc.subjectHybrid
dc.subjectEnergy
dc.subjectEfficiency
dc.subjectPartitioning
dc.subject.lcshArtificial intelligenceen_US
dc.subject.lcshComputational intelligenceen_US
dc.subject.lcshSoft computingen_US
dc.titleUnderstanding the Impact of Hybrid Programming on Software Energy Efficiency
dc.typeThesis
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorTexas State Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US

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