DNA sequence alignment: hybrid parallel programming on a multicore cluster

Autores
Rucci, Enzo; De Giusti, Armando Eduardo; Chichizola, Franco; Naiouf, Marcelo; De Giusti, Laura Cristina
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
DNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expense of a loss of accuracy in the result. This is why heuristics do not ensure that the best alignment is found. For this reason, it is interesting to study how to apply the computer power of different parallel platforms to speed up the sequence alignment process without losing result accuracy. In this article, a new parallelization strategy (HI-M) of Smith-Waterman algorithm on a multi-core cluster is presented, configuring a pipeline with a hybrid communication model. Additionally, a performance analysis is carried out and compared with two previously presented parallel solutions. Finally, experimental results are presented, as well as future research lines.
Facultad de Informática
Materia
Ciencias Informáticas
Bioinformatics
Sequence alignment
Parallel algorithms
Multicore cluster
Pipeline computing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/83228

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network_name_str SEDICI (UNLP)
spelling DNA sequence alignment: hybrid parallel programming on a multicore clusterRucci, EnzoDe Giusti, Armando EduardoChichizola, FrancoNaiouf, MarceloDe Giusti, Laura CristinaCiencias InformáticasBioinformaticsSequence alignmentParallel algorithmsMulticore clusterPipeline computingDNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expense of a loss of accuracy in the result. This is why heuristics do not ensure that the best alignment is found. For this reason, it is interesting to study how to apply the computer power of different parallel platforms to speed up the sequence alignment process without losing result accuracy. In this article, a new parallelization strategy (HI-M) of Smith-Waterman algorithm on a multi-core cluster is presented, configuring a pipeline with a hybrid communication model. Additionally, a performance analysis is carried out and compared with two previously presented parallel solutions. Finally, experimental results are presented, as well as future research lines.Facultad de Informática2011-09-15info: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/10915/83228enginfo:eu-repo/semantics/altIdentifier/isbn/978-1-61804-030-5info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:48:10Zoai:sedici.unlp.edu.ar:10915/83228Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:48:10.66SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv DNA sequence alignment: hybrid parallel programming on a multicore cluster
title DNA sequence alignment: hybrid parallel programming on a multicore cluster
spellingShingle DNA sequence alignment: hybrid parallel programming on a multicore cluster
Rucci, Enzo
Ciencias Informáticas
Bioinformatics
Sequence alignment
Parallel algorithms
Multicore cluster
Pipeline computing
title_short DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_full DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_fullStr DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_full_unstemmed DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_sort DNA sequence alignment: hybrid parallel programming on a multicore cluster
dc.creator.none.fl_str_mv Rucci, Enzo
De Giusti, Armando Eduardo
Chichizola, Franco
Naiouf, Marcelo
De Giusti, Laura Cristina
author Rucci, Enzo
author_facet Rucci, Enzo
De Giusti, Armando Eduardo
Chichizola, Franco
Naiouf, Marcelo
De Giusti, Laura Cristina
author_role author
author2 De Giusti, Armando Eduardo
Chichizola, Franco
Naiouf, Marcelo
De Giusti, Laura Cristina
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Bioinformatics
Sequence alignment
Parallel algorithms
Multicore cluster
Pipeline computing
topic Ciencias Informáticas
Bioinformatics
Sequence alignment
Parallel algorithms
Multicore cluster
Pipeline computing
dc.description.none.fl_txt_mv DNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expense of a loss of accuracy in the result. This is why heuristics do not ensure that the best alignment is found. For this reason, it is interesting to study how to apply the computer power of different parallel platforms to speed up the sequence alignment process without losing result accuracy. In this article, a new parallelization strategy (HI-M) of Smith-Waterman algorithm on a multi-core cluster is presented, configuring a pipeline with a hybrid communication model. Additionally, a performance analysis is carried out and compared with two previously presented parallel solutions. Finally, experimental results are presented, as well as future research lines.
Facultad de Informática
description DNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expense of a loss of accuracy in the result. This is why heuristics do not ensure that the best alignment is found. For this reason, it is interesting to study how to apply the computer power of different parallel platforms to speed up the sequence alignment process without losing result accuracy. In this article, a new parallelization strategy (HI-M) of Smith-Waterman algorithm on a multi-core cluster is presented, configuring a pipeline with a hybrid communication model. Additionally, a performance analysis is carried out and compared with two previously presented parallel solutions. Finally, experimental results are presented, as well as future research lines.
publishDate 2011
dc.date.none.fl_str_mv 2011-09-15
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info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-1-61804-030-5
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
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