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dc.contributor.authorBarrientos, Ricardo
dc.contributor.authorSilva Pavez, Fabián
dc.contributor.authorHernández-García, Ruber
dc.contributor.authorMora, Marco
dc.date.accessioned2023-03-03T13:22:45Z
dc.date.available2023-03-03T13:22:45Z
dc.date.issued2022
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/4461
dc.description.abstractNowadays, searching algorithms are a key component in modern computer science applications. However, traditional approaches of exact search techniques are practicallyan unfeasible solution with the rise of data in high-dimensional databases. The kNN algorithm is frequently used in content based information retrieval systems as it returns similar object sand classifies them. Exhaustive sorting algorithms, such as those based on kNN, can be implemented using a Heap, reducing the computational complexity of the search process. In the present study, we analyze the efficiency of using the Heap data structure on GPUs for solving kNN queries, analyzing the performance of this type of structure as a function of the number of children in the structure. The best results were achieved by increasing the number of children, reaching a speed-up of 1.45x using aternary Heap. The source codes used for the experimentation willbe available to the scientific community in a GitHub repository:https://github.com/ruberhg/GPU-Heaps.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceProceedings - International Conference of the Chilean Computer Science Society, SCCC, 2022, 1-4es_CL
dc.subjectGraphics processing unitses_CL
dc.subjectHardwarees_CL
dc.subjectClassification algorithmses_CL
dc.subjectText categorizationes_CL
dc.subjectSilicones_CL
dc.subjectInformation retrievales_CL
dc.subjectFourth Industrial Revolutiones_CL
dc.titleUsing heaps on GPUes_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias de la Ingenieríaes_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.uriieeexplore.ieee.org/document/10000280es_CL
dc.ucm.doidoi.org/10.1109/SCCC57464.2022.10000280es_CL


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Atribución-NoComercial-SinDerivadas 3.0 Chile
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