Assessing metric structures on GPGPU environments

Autores
Santos, Eder dos; Sofía, Albert A. O.; Uribe Paredes, Roberto
Año de publicación
2015
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Similarity search consists on retrieving objects within a database that are similar or relevant to a particular query. It is a topic of great interest to scientific community because of its many fields of application, such as searching for words and images on the World Wide Web, pattern recognition, detection of plagiarism, multimedia databases, among others. It is modeled through metric spaces, in which objects are represented in a black-box that contains only the distance between objects; calculating the distance function is costly and search systems operate at a high query rate. Metrical structures have been developed to optimize this process; such structures work as indexes and preprocess data to decrease the distance evaluations during the search. Processing large volumes of data makes unfeasible the use of such structures without using parallel processing environments. Technologies based on multi- CPU and GPU architectures are among the most force due to its costs and performance.
XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Search process
Metrics
Parallel
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/50191
Acceder
id SEDICI_13cc66c33053b56903ea0b23b3e854b5
oai_identifier_str oai:sedici.unlp.edu.ar:10915/50191
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Assessing metric structures on GPGPU environmentsSantos, Eder dosSofía, Albert A. O.Uribe Paredes, RobertoCiencias InformáticasSearch processMetricsParallelSimilarity search consists on retrieving objects within a database that are similar or relevant to a particular query. It is a topic of great interest to scientific community because of its many fields of application, such as searching for words and images on the World Wide Web, pattern recognition, detection of plagiarism, multimedia databases, among others. It is modeled through metric spaces, in which objects are represented in a black-box that contains only the distance between objects; calculating the distance function is costly and search systems operate at a high query rate. Metrical structures have been developed to optimize this process; such structures work as indexes and preprocess data to decrease the distance evaluations during the search. Processing large volumes of data makes unfeasible the use of such structures without using parallel processing environments. Technologies based on multi- CPU and GPU architectures are among the most force due to its costs and performance.XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI)2015-10info: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/10915/50191enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-3806-05-6info:eu-repo/semantics/reference/hdl/10915/50028info: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:UNLP2025-09-29T11:03:52Zoai:sedici.unlp.edu.ar:10915/50191Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:03:52.342SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Assessing metric structures on GPGPU environments
title Assessing metric structures on GPGPU environments
spellingShingle Assessing metric structures on GPGPU environments
Santos, Eder dos
Ciencias Informáticas
Search process
Metrics
Parallel
title_short Assessing metric structures on GPGPU environments
title_full Assessing metric structures on GPGPU environments
title_fullStr Assessing metric structures on GPGPU environments
title_full_unstemmed Assessing metric structures on GPGPU environments
title_sort Assessing metric structures on GPGPU environments
dc.creator.none.fl_str_mv Santos, Eder dos
Sofía, Albert A. O.
Uribe Paredes, Roberto
author Santos, Eder dos
author_facet Santos, Eder dos
Sofía, Albert A. O.
Uribe Paredes, Roberto
author_role author
author2 Sofía, Albert A. O.
Uribe Paredes, Roberto
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Search process
Metrics
Parallel
topic Ciencias Informáticas
Search process
Metrics
Parallel
dc.description.none.fl_txt_mv Similarity search consists on retrieving objects within a database that are similar or relevant to a particular query. It is a topic of great interest to scientific community because of its many fields of application, such as searching for words and images on the World Wide Web, pattern recognition, detection of plagiarism, multimedia databases, among others. It is modeled through metric spaces, in which objects are represented in a black-box that contains only the distance between objects; calculating the distance function is costly and search systems operate at a high query rate. Metrical structures have been developed to optimize this process; such structures work as indexes and preprocess data to decrease the distance evaluations during the search. Processing large volumes of data makes unfeasible the use of such structures without using parallel processing environments. Technologies based on multi- CPU and GPU architectures are among the most force due to its costs and performance.
XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
description Similarity search consists on retrieving objects within a database that are similar or relevant to a particular query. It is a topic of great interest to scientific community because of its many fields of application, such as searching for words and images on the World Wide Web, pattern recognition, detection of plagiarism, multimedia databases, among others. It is modeled through metric spaces, in which objects are represented in a black-box that contains only the distance between objects; calculating the distance function is costly and search systems operate at a high query rate. Metrical structures have been developed to optimize this process; such structures work as indexes and preprocess data to decrease the distance evaluations during the search. Processing large volumes of data makes unfeasible the use of such structures without using parallel processing environments. Technologies based on multi- CPU and GPU architectures are among the most force due to its costs and performance.
publishDate 2015
dc.date.none.fl_str_mv 2015-10
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
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/50191
url http://sedici.unlp.edu.ar/handle/10915/50191
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-3806-05-6
info:eu-repo/semantics/reference/hdl/10915/50028
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)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
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_ 1844615907219865600
score 13.070432

Publicaciones similares