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dc.rights.licenseRestricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.
dc.contributorFranklin, W. Randolph
dc.contributorRadke, Richard J., 1974-
dc.contributorWozny, M. J. (Michael J.)
dc.contributorFox, Peter A.
dc.contributor.authorBenedetti, Daniel N
dc.date.accessioned2021-11-03T08:13:27Z
dc.date.available2021-11-03T08:13:27Z
dc.date.created2014-10-08T10:31:01Z
dc.date.issued2014-08
dc.identifier.urihttps://hdl.handle.net/20.500.13015/1185
dc.descriptionAugust 2014
dc.descriptionSchool of Engineering
dc.description.abstractThis thesis presents an efficient ODETLAP implementation for the compression of gridded, multidimensional data. As vast quantities of data are collected for geographic information systems, compression allows for the storage and transmission of larger data sets. Techniques that utilize autocorrelation in all data dimensions allow for greater levels of compression but are more computationally intensive. ODETLAP, Overdetermined Laplacian Approximation, uses a subset of points from the original data set to accurately reconstruct the data. As it expands into higher dimensions, ODETLAP is capable of using relationships in data across multiple dimensions. Various parallelization techniques are used to improve computation time, utilizing CUDA for general purpose programming on a graphics processing unit (GPGPU). An efficient ODETLAP implementation was created directly in GPU memory, successfully avoiding the overhead associated with the transfer of data between GPU memory and main memory.
dc.language.isoENG
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectComputer and systems engineering
dc.titleCUDA-Accelerated ODETLAP : a parallel lossy compression implementation for multidimensional data
dc.typeElectronic thesis
dc.typeThesis
dc.digitool.pid172980
dc.digitool.pid172981
dc.digitool.pid172982
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
dc.description.degreeMS
dc.relation.departmentDept. of Electrical, Computer, and Systems Engineering


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