Optimization of Fast Factorized Backbrojection execution performance

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dc.contributor.authorLidberg, Christian
dc.contributor.authorOlin, Johan
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering, Computing Science (Chalmers)en
dc.date.accessioned2019-07-03T13:07:23Z
dc.date.available2019-07-03T13:07:23Z
dc.date.issued2012
dc.description.abstractReal-time signal processing often requires high computational performance from the signal processing system. In order to increase performance computer systems have moved from the traditional one-core CPU to multi-core systems. This requires, however, parallel software to use all the available performance. It is therefore not only important to have efficient algorithms but also efficient parallel implementations of them. The signal processing for a low-frequency synthetic aperture radar system, used to create high-resolution radar maps of the ground, is studied in this master's thesis. The datasets used to create the maps are often very large and therefore the computational burden is high. The efficient Fast factorized backprojection algorithm is used to create the images but still the images cannot be produced in real-time on a single core system. This thesis describes how the Fast factorized backprojection is optimized and parallelized. OpenMP and vector instructions are used to reach real-time performance on a multi-core platform, for small and medium sized images.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/173241
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectDatorteknik
dc.subjectInformations- och kommunikationsteknik
dc.subjectComputer Engineering
dc.subjectInformation & Communication Technology
dc.titleOptimization of Fast Factorized Backbrojection execution performance
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComputer science – algorithms, languages and logic (MPALG), MSc
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