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dc.contributor.supervisor Thulasiraman, Parimala (Computer Science) Gordon, Richard (Computer Science) en
dc.contributor.author Martin, Daniel Morris
dc.date.accessioned 2007-09-14T15:39:10Z
dc.date.available 2007-09-14T15:39:10Z
dc.date.issued 2007-09-14T15:39:10Z
dc.identifier.uri http://hdl.handle.net/1993/2818
dc.description.abstract Iterative CT reconstruction algorithms are superior to the standard convolution backpropagation (CBP) methods when reconstructing from a small number of views (hence less radiation), but are computationally costly. To reduce the execution time, this work implements and tests a parallel approach to iterative algorithms using a cluster of workstations, which is a low cost system found in many offices and non-academic sites. A previous implementation showed little speedup because of the significant cost of inter-processor communication. In this thesis, several data partitioning methods are examined, including some image tiling methods that exploit the spatial locality demonstrated by local CT. Using these methods, computation can proceed locally, without the need for inter-processor communication during every iteration. A relative speedup of up to 17 times is obtained using 25 processors, demonstrating that good performance can be obtained running computationally intensive CT reconstruction algorithms on distributed memory hardware. en
dc.format.extent 5176303 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.rights info:eu-repo/semantics/openAccess
dc.subject parallel computing en
dc.subject computed tomography en
dc.subject algebraic reconstruction technique en
dc.subject data partitioning en
dc.title Local independence in computed tomography as a basis for parallel computing en
dc.type info:eu-repo/semantics/masterThesis
dc.type master thesis en_US
dc.degree.discipline Computer Science en
dc.contributor.examiningcommittee Li, Ben (Computer Science) Morrison, Jason (Biosystems Engineering) en
dc.degree.level Master of Science (M.Sc.) en
dc.description.note October 2007 en


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