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dc.contributor.advisorBurtscher, Martin
dc.contributor.authorNagarajan, Arthi ( )
dc.date.accessioned2018-09-19T16:06:07Z
dc.date.available2018-09-19T16:06:07Z
dc.date.issued2017-07-24
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/7725
dc.description.abstractExcessive power consumption and cooling costs in computing centers as well as limited battery life in mobile devices make energy optimization an important area of research. In CMOS technology, dynamic energy is primarily consumed when switching from one state to another. In particular, the charging and discharging of long wires consume a significant amount of energy. GPU-based accelerators are widely used to solve many complex data-intensive problems, which tend to transfer large amounts of data to/from main memory. Therefore, GPU data buses contribute a significant portion of the total energy expenditure. As a consequence, encoding the data to minimize bit flips has the potential to greatly reduce the amount of energy consumed by data buses. The existing commercially available solution to reduce bit flips is called Data Bus Inversion (DBI). This thesis introduces more effective bit-flip minimization algorithms, which can eliminate about 9% more bit flips than DBI.
dc.formatText
dc.format.extent47 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectBit-flips
dc.subjectData-transformation algorithms
dc.subject.lcshData miningen_US
dc.subject.lcshDatabase managementen_US
dc.titleData-transformation algorithms for minimizing bit flips on GPU data buses
txstate.documenttypeThesis
dc.contributor.committeeMemberQasem, Apan
dc.contributor.committeeMemberZong, Zillang
thesis.degree.departmentComputer Science
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorTexas State Universityen_US
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
txstate.departmentComputer Science


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