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dc.contributor.advisorElster, Anne Cathrinenb_NO
dc.contributor.authorLien, Geir Jostennb_NO
dc.date.accessioned2014-12-19T13:38:40Z
dc.date.available2014-12-19T13:38:40Z
dc.date.created2012-11-08nb_NO
dc.date.issued2012nb_NO
dc.identifier565905nb_NO
dc.identifierntnudaim:5976nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/252910
dc.description.abstractIn this paper, we present our implementation of an Auto tuning system, written in C++, which incorporate the use of OpenCL kernels. We deploy this approach on different GPU architectures, evaluating the performance of the approach. Our main focus is to easily generate tuned code, that would otherwise require a large amount of empirical testing, and then run it on any kind of device. This is achieved through the auto tuning framework, which will create different kernels, compile and run them on the device and output the best performing kernel on the given platform.BLAS is much used in performance critical applications, and is a good candidate for execution on GPUs due to its potential performance increase. Our implementation was benchmarked on various of test environments, with different GPUs, where we achieved comparable results to the ViennaCL library. We also tested against the native vendor specific BLAS libraries from AMD and NVIDIA.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaim:5976no_NO
dc.subjectMIT informatikkno_NO
dc.subjectKomplekse datasystemerno_NO
dc.titleAuto-tunable GPU BLASnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber63nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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