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dc.contributor.authorHagan, Robert Douglasen_US
dc.date.accessioned2014-03-14T20:41:07Z
dc.date.available2014-03-14T20:41:07Z
dc.date.issued2011-06-24en_US
dc.identifier.otheretd-07052011-105926en_US
dc.identifier.urihttp://hdl.handle.net/10919/33893
dc.description.abstractGPU computing can significantly improve performance by taking advantage of massive parallelism of GPUs for data parallel applications. Computation in visualization applications is suitable for parallelization on the GPU, which can improve performance and interactivity in these applications. If used effectively, multiple GPUs can lead to a significant speedup over a single GPU. However, the use of multiple GPUs requires memory management, scheduling, and load balancing to ensure that a program takes full advantage of available processors. This work presents methods for data-driven and dynamic multi-GPU load balancing using a pipelined approach and a framework for use with different applications. Data-driven load balancing can improve utilization for applications by taking into account past performance for different combinations of input parameters. The dynamic load balancing method based on buffer fullness can adjust to workload changes at runtime to gain an additional performance improvement. This work provides a framework for load balancing to account for differing characteristics of applications. Implementation of a multi-GPU data structure allows for use of these load balancing methods in the framework. The effectiveness of the framework is demonstrated with performance results from interactive visualization that shows a significant speedup due to load balancing.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartHagan_RD_T_2011.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectLoad Balancingen_US
dc.subjectMulti-GPU Computingen_US
dc.subjectRenderingen_US
dc.subjectSimulationen_US
dc.titleMulti-GPU Load Balancing for Simulation and Renderingen_US
dc.typeThesisen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Scienceen_US
dc.contributor.committeechairCao, Yongen_US
dc.contributor.committeememberNorth, Christopher L.en_US
dc.contributor.committeememberTilevich, Elien_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07052011-105926/en_US
dc.date.sdate2011-07-05en_US
dc.date.rdate2011-08-04
dc.date.adate2011-08-04en_US


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