Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data

The k-th nearest neighbour problem for 3D data has been widely studied, nevertheless, the surge of using GPU (Graphical Processing Unit) as general-purpose computing units opens up the need to design and implement new algorithms, that allow us to get results more rapidly than using conventional algo...

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Detalles Bibliográficos
Autores principales: Sepúlveda, Exequiel, Muñoz, Felipe
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2010
Materias:
Ciencias Informáticas
3D
GPU
CPU
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/152633
http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-hpc-05.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-152633
record_format dspace
spelling I19-R120-10915-1526332023-05-09T20:04:17Z http://sedici.unlp.edu.ar/handle/10915/152633 http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-hpc-05.pdf issn:1851-9326 Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data Sepúlveda, Exequiel Muñoz, Felipe 2010 2010 2023-05-09T13:42:53Z en Ciencias Informáticas 3D GPU CPU The k-th nearest neighbour problem for 3D data has been widely studied, nevertheless, the surge of using GPU (Graphical Processing Unit) as general-purpose computing units opens up the need to design and implement new algorithms, that allow us to get results more rapidly than using conventional algorithms. The main advantage of GPU is its great computing capacity for parallel computing. This is due to an architecture that contemplates a great number of processing cores originally designed to graphics processing and that can currently be used for other purposes such as high performance cientific calculation. Sociedad Argentina de Informática e Investigación Operativa Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 3229-3233
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
3D
GPU
CPU
spellingShingle Ciencias Informáticas
3D
GPU
CPU
Sepúlveda, Exequiel
Muñoz, Felipe
Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
topic_facet Ciencias Informáticas
3D
GPU
CPU
description The k-th nearest neighbour problem for 3D data has been widely studied, nevertheless, the surge of using GPU (Graphical Processing Unit) as general-purpose computing units opens up the need to design and implement new algorithms, that allow us to get results more rapidly than using conventional algorithms. The main advantage of GPU is its great computing capacity for parallel computing. This is due to an architecture that contemplates a great number of processing cores originally designed to graphics processing and that can currently be used for other purposes such as high performance cientific calculation.
format Objeto de conferencia
Objeto de conferencia
author Sepúlveda, Exequiel
Muñoz, Felipe
author_facet Sepúlveda, Exequiel
Muñoz, Felipe
author_sort Sepúlveda, Exequiel
title Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
title_short Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
title_full Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
title_fullStr Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
title_full_unstemmed Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
title_sort extended abstract: hybrid knn algorithm using cpu and gpu applied on 3d data
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/152633
http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-hpc-05.pdf
work_keys_str_mv AT sepulvedaexequiel extendedabstracthybridknnalgorithmusingcpuandgpuappliedon3ddata
AT munozfelipe extendedabstracthybridknnalgorithmusingcpuandgpuappliedon3ddata
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