Smith-Waterman algorithm on heterogeneous systems: A case study

Autores
Rucci, Enzo; De Giusti, Armando Eduardo; Naiouf, Marcelo; García Sánchez, Carlos; Botella, Juan Guillermo; Prieto-Matías, Manuel
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. However, SW is expensive in terms of both execution time and memory usage, which makes it impractical in many applications. Some heuristics are possible but at the expense of losing sensitivity. Fortunately, previous research have shown that new computing platforms such as GPUs and FPGAs are able to accelerate SW and achieve impressive speedups. In this paper we have explored SW acceleration on a heterogeneous platform equipped with an Intel Xeon Phi coprocessor. Our evaluation, using the well-known Swiss-Prot database as a benchmark, has shown that a hybrid CPU-Phi heterogeneous system is able to achieve competitive performance (62.6 GCUPS), even with moderate low-level optimisations.
Facultad de Informática
Materia
Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous 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:10915/82886
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/82886
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Smith-Waterman algorithm on heterogeneous systems: A case studyRucci, EnzoDe Giusti, Armando EduardoNaiouf, MarceloGarcía Sánchez, CarlosBotella, Juan GuillermoPrieto-Matías, ManuelCiencias InformáticasBioinformaticsSmith-WatermanHPCIntel Xeon PhiHeterogeneous computingThe well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. However, SW is expensive in terms of both execution time and memory usage, which makes it impractical in many applications. Some heuristics are possible but at the expense of losing sensitivity. Fortunately, previous research have shown that new computing platforms such as GPUs and FPGAs are able to accelerate SW and achieve impressive speedups. In this paper we have explored SW acceleration on a heterogeneous platform equipped with an Intel Xeon Phi coprocessor. Our evaluation, using the well-known Swiss-Prot database as a benchmark, has shown that a hybrid CPU-Phi heterogeneous system is able to achieve competitive performance (62.6 GCUPS), even with moderate low-level optimisations.Facultad de Informática2014-09-25info: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/10915/82886enginfo:eu-repo/semantics/altIdentifier/isbn/978-1-4799-5548-0info:eu-repo/semantics/altIdentifier/doi/10.1109/CLUSTER.2014.6968784info: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:UNLP2025-09-29T11:15:36Zoai:sedici.unlp.edu.ar:10915/82886Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:15:37.192SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Smith-Waterman algorithm on heterogeneous systems: A case study
title Smith-Waterman algorithm on heterogeneous systems: A case study
spellingShingle Smith-Waterman algorithm on heterogeneous systems: A case study
Rucci, Enzo
Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
title_short Smith-Waterman algorithm on heterogeneous systems: A case study
title_full Smith-Waterman algorithm on heterogeneous systems: A case study
title_fullStr Smith-Waterman algorithm on heterogeneous systems: A case study
title_full_unstemmed Smith-Waterman algorithm on heterogeneous systems: A case study
title_sort Smith-Waterman algorithm on heterogeneous systems: A case study
dc.creator.none.fl_str_mv Rucci, Enzo
De Giusti, Armando Eduardo
Naiouf, Marcelo
García Sánchez, Carlos
Botella, Juan Guillermo
Prieto-Matías, Manuel
author Rucci, Enzo
author_facet Rucci, Enzo
De Giusti, Armando Eduardo
Naiouf, Marcelo
García Sánchez, Carlos
Botella, Juan Guillermo
Prieto-Matías, Manuel
author_role author
author2 De Giusti, Armando Eduardo
Naiouf, Marcelo
García Sánchez, Carlos
Botella, Juan Guillermo
Prieto-Matías, Manuel
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
topic Ciencias Informáticas
Bioinformatics
Smith-Waterman
HPC
Intel Xeon Phi
Heterogeneous computing
dc.description.none.fl_txt_mv The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. However, SW is expensive in terms of both execution time and memory usage, which makes it impractical in many applications. Some heuristics are possible but at the expense of losing sensitivity. Fortunately, previous research have shown that new computing platforms such as GPUs and FPGAs are able to accelerate SW and achieve impressive speedups. In this paper we have explored SW acceleration on a heterogeneous platform equipped with an Intel Xeon Phi coprocessor. Our evaluation, using the well-known Swiss-Prot database as a benchmark, has shown that a hybrid CPU-Phi heterogeneous system is able to achieve competitive performance (62.6 GCUPS), even with moderate low-level optimisations.
Facultad de Informática
description The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. However, SW is expensive in terms of both execution time and memory usage, which makes it impractical in many applications. Some heuristics are possible but at the expense of losing sensitivity. Fortunately, previous research have shown that new computing platforms such as GPUs and FPGAs are able to accelerate SW and achieve impressive speedups. In this paper we have explored SW acceleration on a heterogeneous platform equipped with an Intel Xeon Phi coprocessor. Our evaluation, using the well-known Swiss-Prot database as a benchmark, has shown that a hybrid CPU-Phi heterogeneous system is able to achieve competitive performance (62.6 GCUPS), even with moderate low-level optimisations.
publishDate 2014
dc.date.none.fl_str_mv 2014-09-25
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/10915/82886
url http://sedici.unlp.edu.ar/handle/10915/82886
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-1-4799-5548-0
info:eu-repo/semantics/altIdentifier/doi/10.1109/CLUSTER.2014.6968784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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)
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instname_str Universidad Nacional de La Plata
instacron_str UNLP
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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