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dc.contributor.advisorBurtscher, Martin
dc.contributor.authorTaheri, Saeed ( )
dc.date.accessioned2014-12-19T17:52:56Z
dc.date.available2014-12-19T17:52:56Z
dc.date.issued2014-12
dc.identifier.citationTaheri, S. (2014). A tool for automatic suggestions for irregular GPU kernel optimization (Unpublished thesis). Texas State University, San Marcos, Texas.
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/5380
dc.description.abstract

Future computing systems, from handhelds all the way to supercomputers, will be more parallel and more heterogeneous than today’s systems to provide more performance without an increase in power consumption. Therefore, GPUs are increasingly being used to accelerate general-purpose applications, including applications with data-dependent, irregular memory access patterns and control flow.

The growing complexity, non-uniformity, heterogeneity, and parallelism will make these systems, i.e., GPGPU-accelerated systems, progressively more difficult to program. In the foreseeable future, the vast majority of programmers will no longer be able to extract additional performance or energy-savings from next-generation systems because their programming will be too difficult, i.e., the programmer will no longer possess the necessary expertise to understand and exploit the systems effectively. In this project, the characteristics of GPU codes will be quantified and, based on these metrics, different optimization suggestions will be made.

dc.formatText
dc.format.extent63 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectGPU
dc.subjectOptimization
dc.subjectIrregular
dc.subject.lcshComputer scienceen_US
dc.subject.lcshGraphics processing unitsen_US
dc.subject.lcshParallel computersen_US
dc.subject.lcshParallel processing (Electronic computers)en_US
dc.titleA Tool for Automatic Suggestions for Irregular GPU Kernel Optimization
txstate.documenttypeThesis
dc.contributor.committeeMemberQasem, Apan
dc.contributor.committeeMemberZong, Ziliang
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorTexas State Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
txstate.departmentComputer Science


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