Accelerated High-Performance Compressive Sensing using the Graphics Processing Unit

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dc.contributor.advisorYin, Wotao
dc.creatorReyna, Nabor
dc.date.accessioned2013-03-08T00:38:00Z
dc.date.available2013-03-08T00:38:00Z
dc.date.issued2011
dc.description.abstractThis thesis demonstrates the advantages of new practical implementations of compressive sensing (CS) algorithms tailored for the graphics processing unit (CPU) using a software platform called Jacket. There exist many applications which utilize CS including medical imaging, signal processing and data acquisition which have benefited from advancements in CS. However, as problems become larger not only do they become more difficult to solve but also more computationally expensive. In light of tins, existing CS algorithms are augmented for practical use on the CPU, reaping performance gains from the highly parallel architecture of the GPU. I discuss the issues associated with this transition and analyze the effects of such a movement, as well as provide results exhibiting advantages of using CPU-based methods.
dc.format.extent58 p.en_US
dc.format.mimetypeapplication/pdf
dc.identifier.callnoTHESIS MATH. SCI. 2011 REYNA
dc.identifier.citationReyna, Nabor. "Accelerated High-Performance Compressive Sensing using the Graphics Processing Unit." (2011) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/70407">https://hdl.handle.net/1911/70407</a>.
dc.identifier.digitalReynaNen_US
dc.identifier.urihttps://hdl.handle.net/1911/70407
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectApplied sciences
dc.subjectApplied mathematics
dc.titleAccelerated High-Performance Compressive Sensing using the Graphics Processing Unit
dc.typeThesis
dc.type.materialText
thesis.degree.departmentMathematical Sciences
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Arts
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