Accelerated coplanar facet radio synthesis imaging

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dc.contributor.advisorGain, Jamesen_ZA
dc.contributor.advisorSmirnov, Olegen_ZA
dc.contributor.advisorTasse, Cyrilen_ZA
dc.contributor.authorHugo, Benjaminen_ZA
dc.date.accessioned2016-07-20T12:35:20Z
dc.date.available2016-07-20T12:35:20Z
dc.date.issued2016en_ZA
dc.description.abstractImaging in radio astronomy entails the Fourier inversion of the relation between the sampled spatial coherence of an electromagnetic field and the intensity of its emitting source. This inversion is normally computed by performing a convolutional resampling step and applying the Inverse Fast Fourier Transform, because this leads to computational savings. Unfortunately, the resulting planar approximation of the sky is only valid over small regions. When imaging over wider fields of view, and in particular using telescope arrays with long non-East-West components, significant distortions are introduced in the computed image. We propose a coplanar faceting algorithm, where the sky is split up into many smaller images. Each of these narrow-field images are further corrected using a phase-correcting tech- nique known as w-projection. This eliminates the projection error along the edges of the facets and ensures approximate coplanarity. The combination of faceting and w-projection approaches alleviates the memory constraints of previous w-projection implementations. We compared the scaling performance of both single and double precision resampled images in both an optimized multi-threaded CPU implementation and a GPU implementation that uses a memory-access- limiting work distribution strategy. We found that such a w-faceting approach scales slightly better than a traditional w-projection approach on GPUs. We also found that double precision resampling on GPUs is about 71% slower than its single precision counterpart, making double precision resampling on GPUs less power efficient than CPU-based double precision resampling. Lastly, we have seen that employing only single precision in the resampling summations produces significant error in continuum images for a MeerKAT-sized array over long observations, especially when employing the large convolution filters necessary to create large images.en_ZA
dc.identifier.apacitationHugo, B. (2016). <i>Accelerated coplanar facet radio synthesis imaging</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/20543en_ZA
dc.identifier.chicagocitationHugo, Benjamin. <i>"Accelerated coplanar facet radio synthesis imaging."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 2016. http://hdl.handle.net/11427/20543en_ZA
dc.identifier.citationHugo, B. 2016. Accelerated coplanar facet radio synthesis imaging. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Hugo, Benjamin AB - Imaging in radio astronomy entails the Fourier inversion of the relation between the sampled spatial coherence of an electromagnetic field and the intensity of its emitting source. This inversion is normally computed by performing a convolutional resampling step and applying the Inverse Fast Fourier Transform, because this leads to computational savings. Unfortunately, the resulting planar approximation of the sky is only valid over small regions. When imaging over wider fields of view, and in particular using telescope arrays with long non-East-West components, significant distortions are introduced in the computed image. We propose a coplanar faceting algorithm, where the sky is split up into many smaller images. Each of these narrow-field images are further corrected using a phase-correcting tech- nique known as w-projection. This eliminates the projection error along the edges of the facets and ensures approximate coplanarity. The combination of faceting and w-projection approaches alleviates the memory constraints of previous w-projection implementations. We compared the scaling performance of both single and double precision resampled images in both an optimized multi-threaded CPU implementation and a GPU implementation that uses a memory-access- limiting work distribution strategy. We found that such a w-faceting approach scales slightly better than a traditional w-projection approach on GPUs. We also found that double precision resampling on GPUs is about 71% slower than its single precision counterpart, making double precision resampling on GPUs less power efficient than CPU-based double precision resampling. Lastly, we have seen that employing only single precision in the resampling summations produces significant error in continuum images for a MeerKAT-sized array over long observations, especially when employing the large convolution filters necessary to create large images. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Accelerated coplanar facet radio synthesis imaging TI - Accelerated coplanar facet radio synthesis imaging UR - http://hdl.handle.net/11427/20543 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20543
dc.identifier.vancouvercitationHugo B. Accelerated coplanar facet radio synthesis imaging. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20543en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherComputer Scienceen_ZA
dc.titleAccelerated coplanar facet radio synthesis imagingen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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