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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/83228
Ver los metadatos del registro completo
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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 |
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2011-09-15 |
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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 |
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eng |
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