{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:math_etds-1014"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:math_etds-1014","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA","abstract":"In this thesis we present the first, to our knowledge, implementation and performance analysis of Hermite methods on GPU accelerated systems. We give analytic background for Hermite methods; give implementations of the Hermite methods on traditional CPU systems as well as on GPUs; give the reader background on basic CUDA programming for GPUs; discuss performance characteristics of GPUs; we give recommended design choices for GPU implementations of Hermite methods; and present and discuss examples which illustrate the effect these design choices have on performance. 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Lastly, we present areas of future research that may yield increased performance for Hermite methods on GPUs.","abstract_has_math":false,"creators":["Dye, Evan T."],"institution":null,"degree_name":"Mathematics","degree_level":"Masters","degree_discipline":"Mathematics & Statistics","degree_department":null,"school":null,"contributors":["Appel&ouml;, Daniel","Daniel Appelö","Stephen Lau","Jens Lorenz"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-28T08:00:00Z","date_published":"2015-01-28T08:00:00Z","updated_at":"2026-07-24T05:27:37Z","subjects":["GPU","Hermite","Optimization","OpenCL","CUDA","Computational","Performance","PDE","Partial Differential Equation","Analysis","Applied Mathematics","Mathematics","Numerical","NVIDIA"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalrepository.unm.edu/math_etds/15"],"render_values":[{"text":"https://digitalrepository.unm.edu/math_etds/15","href":"https://digitalrepository.unm.edu/math_etds/15","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/1928/25739","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Appel&ouml;, Daniel","Daniel Appelö","Stephen Lau","Jens Lorenz"]},{"key":"dc:creator","label":"Author","values":["Dye, Evan T."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics & Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters","Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Mathematics"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["GPU","Hermite","Optimization","OpenCL","CUDA","Computational","Performance","PDE","Partial Differential Equation","Analysis","Applied Mathematics","Mathematics","Numerical","NVIDIA"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/1928/25739","https://digitalrepository.unm.edu/math_etds/15"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In this thesis we present the first, to our knowledge, implementation and performance analysis of Hermite methods on GPU accelerated systems. 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We give analytic background for Hermite methods; give implementations of the Hermite methods on traditional CPU systems as well as on GPUs; give the reader background on basic CUDA programming for GPUs; discuss performance characteristics of GPUs; we give recommended design choices for GPU implementations of Hermite methods; and present and discuss examples which illustrate the effect these design choices have on performance. 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