Wavelet transform for large scale image processing on modern microprocessors

In this paper we discuss several issues relevant to the vectorization of a 2-D Discrete Wavelet Transform on current microprocessors. Our research is based on previous studies about the efficient exploitation of the memory hierarchy, due to its tremendous impact on performance. We have extended this...

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Detalles Bibliográficos
Autores: Chaver Martínez, Daniel Ángel, Tenllado Van Der Reijden, Christian Tomás, Piñuel Moreno, Luis, Tirado Fernández, José Francisco
Tipo de recurso: capítulo de libro
Fecha de publicación:2003
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/60900
Acceso en línea:https://hdl.handle.net/20.500.14352/60900
Access Level:acceso abierto
Palabra clave:004
Performance
Informática (Informática)
Programación de ordenadores (Informática)
1203.17 Informática
1203.23 Lenguajes de Programación
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oai_identifier_str oai:docta.ucm.es:20.500.14352/60900
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spelling Wavelet transform for large scale image processing on modern microprocessorsChaver Martínez, Daniel ÁngelTenllado Van Der Reijden, Christian TomásPiñuel Moreno, LuisTirado Fernández, José Francisco004PerformanceInformática (Informática)Programación de ordenadores (Informática)1203.17 Informática1203.23 Lenguajes de ProgramaciónIn this paper we discuss several issues relevant to the vectorization of a 2-D Discrete Wavelet Transform on current microprocessors. Our research is based on previous studies about the efficient exploitation of the memory hierarchy, due to its tremendous impact on performance. We have extended this work with a more detailed analysis based on hardware performance counters and a study of vectorization, in particular, we have used the Intel Pentium SSE instruction set. Most of our optimizations are performed at source code level to allow automatic vectorization, though some compiler intrinsic functions have been introduced to enhance performance. Taking into account the abstraction at which the optimizations are performed, the results obtained on an Intel Pentium III microprocessor are quite satisfactory, even though further improvement can be obtained by a more extensive use of compiler intrinsics.Springer-Verlag BerlinUniversidad Complutense de Madrid20032003-01-0120032003-01-01book parthttp://purl.org/coar/resource_type/c_3248info:eu-repo/semantics/bookPartapplication/pdfhttps://hdl.handle.net/20.500.14352/60900reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/609002026-06-02T12:44:21Z
dc.title.none.fl_str_mv Wavelet transform for large scale image processing on modern microprocessors
title Wavelet transform for large scale image processing on modern microprocessors
spellingShingle Wavelet transform for large scale image processing on modern microprocessors
Chaver Martínez, Daniel Ángel
004
Performance
Informática (Informática)
Programación de ordenadores (Informática)
1203.17 Informática
1203.23 Lenguajes de Programación
title_short Wavelet transform for large scale image processing on modern microprocessors
title_full Wavelet transform for large scale image processing on modern microprocessors
title_fullStr Wavelet transform for large scale image processing on modern microprocessors
title_full_unstemmed Wavelet transform for large scale image processing on modern microprocessors
title_sort Wavelet transform for large scale image processing on modern microprocessors
dc.creator.none.fl_str_mv Chaver Martínez, Daniel Ángel
Tenllado Van Der Reijden, Christian Tomás
Piñuel Moreno, Luis
Tirado Fernández, José Francisco
author Chaver Martínez, Daniel Ángel
author_facet Chaver Martínez, Daniel Ángel
Tenllado Van Der Reijden, Christian Tomás
Piñuel Moreno, Luis
Tirado Fernández, José Francisco
author_role author
author2 Tenllado Van Der Reijden, Christian Tomás
Piñuel Moreno, Luis
Tirado Fernández, José Francisco
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 004
Performance
Informática (Informática)
Programación de ordenadores (Informática)
1203.17 Informática
1203.23 Lenguajes de Programación
topic 004
Performance
Informática (Informática)
Programación de ordenadores (Informática)
1203.17 Informática
1203.23 Lenguajes de Programación
description In this paper we discuss several issues relevant to the vectorization of a 2-D Discrete Wavelet Transform on current microprocessors. Our research is based on previous studies about the efficient exploitation of the memory hierarchy, due to its tremendous impact on performance. We have extended this work with a more detailed analysis based on hardware performance counters and a study of vectorization, in particular, we have used the Intel Pentium SSE instruction set. Most of our optimizations are performed at source code level to allow automatic vectorization, though some compiler intrinsic functions have been introduced to enhance performance. Taking into account the abstraction at which the optimizations are performed, the results obtained on an Intel Pentium III microprocessor are quite satisfactory, even though further improvement can be obtained by a more extensive use of compiler intrinsics.
publishDate 2003
dc.date.none.fl_str_mv 2003
2003-01-01
2003
2003-01-01
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/60900
url https://hdl.handle.net/20.500.14352/60900
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer-Verlag Berlin
publisher.none.fl_str_mv Springer-Verlag Berlin
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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