Spatial subdivision for parallel ray casting/tracing

buir.advisorAykanat, Cevdet
dc.contributor.authorİşler, Veysi
dc.date.accessioned2016-01-08T20:19:33Z
dc.date.available2016-01-08T20:19:33Z
dc.date.issued1995
dc.descriptionAnkara : Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 1995.en_US
dc.descriptionThesis (Ph. D.) -- Bilkent University, 1995.en_US
dc.descriptionIncludes bibliographical references leaves 82-85.en_US
dc.description.abstractRay casting/tracing has been extensively studied for a long time, since it is an elegant way of producing realistic images. However, it is a computationally intensive algorithm. In this study, a taxonomy of parallel ray casting/tracing algorithms is presented cind the primary parallel ray casting/tracing systems are discussed and criticized. This work mainly focuses on the utilization of spatial subdivision technique for ray casting/tracing on a distributed-memory MIMD parallel computer. In this research, the reason for the use of parallel computers is not only the processing power but also the large memory space provided by them. The spatial subdivision technique has been adapted to parallel ray casting/tracing to decompose a three-dimensional complex scene that may not fit into the local memory of a single processor. The decomposition method achieves an even distribution of scene objects while allowing to exploit graphical coherence. Additionally, the decomposition method produces three-dimensional volumes which are mapped inexpensively to the processors so that the objects within adjacent volumes are stored in the local memories of close processors to decrease interprocessor communication cost. Then, the developed decomposition and mapping methods have been parallelized efficiently to reduce the preprocessing overhead. Finally, a splitting plane concept (called “jaggy splitting plane”) has been proposed to accomplish full utilization of the memory space of processors. Jaggy splitting plane avoids the shared objects which are the major sources of inefficient utilization of both memory and processing power. The proposed parallel algorithms have been implemented on the Intel iPSC/2 hypercube multicomputer (distributed-memory MIMD).en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T20:19:33Z (GMT). No. of bitstreams: 1 1.pdf: 78510 bytes, checksum: d85492f20c2362aa2bcf4aad49380397 (MD5)en
dc.description.statementofresponsibilityİşler, Veysien_US
dc.format.extentxii, 86 leavesen_US
dc.identifier.urihttp://hdl.handle.net/11693/18462
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectRay castingen_US
dc.subjectRay tracingen_US
dc.subjectSpatial subdivisionen_US
dc.subjectBinary spatial partitioning (BSP)en_US
dc.subjectSplitting planeen_US
dc.subjectHypercube topologyen_US
dc.subjectParallel processingen_US
dc.subject.lccQA76.58 .I85 1995en_US
dc.subject.lcshParallel processing (Electronic computers).en_US
dc.subject.lcshComputer algorithms.en_US
dc.subject.lcshImage processing--Digital techniques.en_US
dc.subject.lcshComputer vision.en_US
dc.subject.lcshGraph theory.en_US
dc.subject.lcshParallel computers.en_US
dc.titleSpatial subdivision for parallel ray casting/tracingen_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelDoctoral
thesis.degree.namePh.D. (Doctor of Philosophy)

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