Efficient similarity search on multimedia databases
- Autores
- Lopresti, Mariela; Miranda, Natalia Carolina; Piccoli, María Fabiana; Reyes, Nora Susana
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Manipulating and retrieving multimedia data has received increasing attention with the advent of cloud storage facilities. The ability of querying by similarity over large data collections is mandatory to improve storage and user interfaces. But, all of them are expensive operations to solve only in CPU; thus, it is convenient to take into account High Performance Computing (HPC) techniques in their solutions. The Graphics Processing Unit (GPU) as an alternative HPC device has been increasingly used to speedup certain computing processes. This work introduces a pure GPU architecture to build the Permutation Index and to solve approximate similarity queries on multimedia databases. The empirical results of each implementation have achieved different level of speedup which are related with characteristics of GPU and the particular database used.
Eje: Workshop Bases de datos y minería de datos (WBDDM)
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Multimedia database
Metric Space
Approximate Similarity Query
High Performance Computing
Graphics Processing Unit
Metrics
base de datos
Data mining - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23751
Ver los metadatos del registro completo
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Efficient similarity search on multimedia databasesLopresti, MarielaMiranda, Natalia CarolinaPiccoli, María FabianaReyes, Nora SusanaCiencias InformáticasMultimedia databaseMetric SpaceApproximate Similarity QueryHigh Performance ComputingGraphics Processing UnitMetricsbase de datosData miningManipulating and retrieving multimedia data has received increasing attention with the advent of cloud storage facilities. The ability of querying by similarity over large data collections is mandatory to improve storage and user interfaces. But, all of them are expensive operations to solve only in CPU; thus, it is convenient to take into account High Performance Computing (HPC) techniques in their solutions. The Graphics Processing Unit (GPU) as an alternative HPC device has been increasingly used to speedup certain computing processes. This work introduces a pure GPU architecture to build the Permutation Index and to solve approximate similarity queries on multimedia databases. The empirical results of each implementation have achieved different level of speedup which are related with characteristics of GPU and the particular database used.Eje: Workshop Bases de datos y minería de datos (WBDDM)Red de Universidades con Carreras en Informática (RedUNCI)2012-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23751enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:35Zoai:sedici.unlp.edu.ar:10915/23751Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:35.817SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Efficient similarity search on multimedia databases |
title |
Efficient similarity search on multimedia databases |
spellingShingle |
Efficient similarity search on multimedia databases Lopresti, Mariela Ciencias Informáticas Multimedia database Metric Space Approximate Similarity Query High Performance Computing Graphics Processing Unit Metrics base de datos Data mining |
title_short |
Efficient similarity search on multimedia databases |
title_full |
Efficient similarity search on multimedia databases |
title_fullStr |
Efficient similarity search on multimedia databases |
title_full_unstemmed |
Efficient similarity search on multimedia databases |
title_sort |
Efficient similarity search on multimedia databases |
dc.creator.none.fl_str_mv |
Lopresti, Mariela Miranda, Natalia Carolina Piccoli, María Fabiana Reyes, Nora Susana |
author |
Lopresti, Mariela |
author_facet |
Lopresti, Mariela Miranda, Natalia Carolina Piccoli, María Fabiana Reyes, Nora Susana |
author_role |
author |
author2 |
Miranda, Natalia Carolina Piccoli, María Fabiana Reyes, Nora Susana |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Multimedia database Metric Space Approximate Similarity Query High Performance Computing Graphics Processing Unit Metrics base de datos Data mining |
topic |
Ciencias Informáticas Multimedia database Metric Space Approximate Similarity Query High Performance Computing Graphics Processing Unit Metrics base de datos Data mining |
dc.description.none.fl_txt_mv |
Manipulating and retrieving multimedia data has received increasing attention with the advent of cloud storage facilities. The ability of querying by similarity over large data collections is mandatory to improve storage and user interfaces. But, all of them are expensive operations to solve only in CPU; thus, it is convenient to take into account High Performance Computing (HPC) techniques in their solutions. The Graphics Processing Unit (GPU) as an alternative HPC device has been increasingly used to speedup certain computing processes. This work introduces a pure GPU architecture to build the Permutation Index and to solve approximate similarity queries on multimedia databases. The empirical results of each implementation have achieved different level of speedup which are related with characteristics of GPU and the particular database used. Eje: Workshop Bases de datos y minería de datos (WBDDM) Red de Universidades con Carreras en Informática (RedUNCI) |
description |
Manipulating and retrieving multimedia data has received increasing attention with the advent of cloud storage facilities. The ability of querying by similarity over large data collections is mandatory to improve storage and user interfaces. But, all of them are expensive operations to solve only in CPU; thus, it is convenient to take into account High Performance Computing (HPC) techniques in their solutions. The Graphics Processing Unit (GPU) as an alternative HPC device has been increasingly used to speedup certain computing processes. This work introduces a pure GPU architecture to build the Permutation Index and to solve approximate similarity queries on multimedia databases. The empirical results of each implementation have achieved different level of speedup which are related with characteristics of GPU and the particular database used. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-10 |
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 |
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http://sedici.unlp.edu.ar/handle/10915/23751 |
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http://sedici.unlp.edu.ar/handle/10915/23751 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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