The implementation of parallel computation on CPU and GPU

dc.contributor.authorXia, Kun
dc.date.accessioned2019-11-15T13:23:57Z
dc.date.available2019-11-15T13:23:57Z
dc.date.issued2017
dc.date.updated2017-09-05T16:30:58Z
dc.description.abstractHigh performance computations have never been failed to attract people since the first computer was created. Before using parallel computations, people tried to increase the performance of single core processor. But the large power consumption and heat releasing became to the biggest performance limit for single core processor. Therefore, the technology of parallel programming was introduced couple years ago and replaced the role of single core processor. Parallel computation is the algorithm that control multiple operations simultaneously. It can be implement not only on multiple processor device, but also implement on single processor. This study is about researching implementation of parallel computing with C. After introducing the basic idea and structures of parallel computation, the implementation of parallel computation will be created with tree algorithm. On the single processor like CPU, parallel computation is applied with pthread function. And for the multiple processor like GPU, CUDA is the best choice for us. Meanwhile, the serial function is also needed for testing the correctness of parallel computing functions and performance analysis.en_US
dc.description.advisorLi, Xiaoming
dc.description.degreeM.S.
dc.description.departmentUniversity of Delaware, Department of Electrical and Computer Engineering
dc.identifier.doihttps://doi.org/10.58088/ws2g-d546
dc.identifier.unique1127648887
dc.identifier.urihttp://udspace.udel.edu/handle/19716/24724
dc.language.rfc3066en
dc.publisherUniversity of Delawareen_US
dc.relation.urihttps://search.proquest.com/docview/1975370076?accountid=10457
dc.titleThe implementation of parallel computation on CPU and GPUen_US
dc.typeThesisen_US

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