Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data
- Autores
- Sepúlveda, Exequiel; Muñoz, Felipe
- Año de publicación
- 2010
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- 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 - Materia
-
Ciencias Informáticas
3D
GPU
CPU - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/152633
Ver los metadatos del registro completo
| id |
SEDICI_d5d8ddf79dffa41903dea660848099cf |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/152633 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D dataSepúlveda, ExequielMuñoz, FelipeCiencias Informáticas3DGPUCPUThe 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 Operativa2010info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf3229-3233http://sedici.unlp.edu.ar/handle/10915/152633enginfo:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-hpc-05.pdfinfo:eu-repo/semantics/altIdentifier/issn/1851-9326info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:39:27Zoai:sedici.unlp.edu.ar:10915/152633Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:39:27.24SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data |
| title |
Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data |
| spellingShingle |
Extended Abstract: Hybrid KNN Algorithm using CPU and GPU applied on 3D data Sepúlveda, Exequiel Ciencias Informáticas 3D GPU CPU |
| 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 |
| dc.creator.none.fl_str_mv |
Sepúlveda, Exequiel Muñoz, Felipe |
| author |
Sepúlveda, Exequiel |
| author_facet |
Sepúlveda, Exequiel Muñoz, Felipe |
| author_role |
author |
| author2 |
Muñoz, Felipe |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas 3D GPU CPU |
| topic |
Ciencias Informáticas 3D GPU CPU |
| dc.description.none.fl_txt_mv |
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 |
| 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. |
| publishDate |
2010 |
| dc.date.none.fl_str_mv |
2010 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
| format |
conferenceObject |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/152633 |
| url |
http://sedici.unlp.edu.ar/handle/10915/152633 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-hpc-05.pdf info:eu-repo/semantics/altIdentifier/issn/1851-9326 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| dc.format.none.fl_str_mv |
application/pdf 3229-3233 |
| dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
| reponame_str |
SEDICI (UNLP) |
| collection |
SEDICI (UNLP) |
| instname_str |
Universidad Nacional de La Plata |
| instacron_str |
UNLP |
| institution |
UNLP |
| repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
| repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
| _version_ |
1844616268225708032 |
| score |
13.070432 |