An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures

Autores
Rucci, Enzo; García, Carlos; Botella, Guillermo; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; Prieto Matías, Manuel
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Summary Alignment is essential in many areas such as biological, chemical and criminal forensics. The well-known Smith-Waterman (SW) algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. There are several implementations that take advantage of computing parallelization, such as manycores, FPGAS or GPUS, in order to reduce the alignment effort. In this research, we adapt, develop and tune the SW algorithm named SWIMM on a heterogeneous platform based on Intel's Xeon and Xeon Phi coprocessor. SWIMM is a free tool available in a public git repository https://github.com/enzorucci/SWIMM. We efficiently exploit data and thread-level parallelism, reaching up to 380 GCUPS on heterogeneous architecture, 350 GCUPS for the isolated Xeon and 50 GCUPS on Xeon Phi. Despite the heterogeneous implementation obtaining the best performance, it is also the most energy-demanding. In fact, we also present a trade-off analysis between performance and power consumption. The greenest configuration is based on an isolated multicore system that exploits AVX2 instruction set architecture reaching 1.5 GCUPS/Watts.
Fil: Rucci, Enzo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: García, Carlos. Universidad Complutense de Madrid; España
Fil: Botella, Guillermo. Universidad Complutense de Madrid; España
Fil: de Giusti, Armando Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: Naiouf, Ricardo Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: Prieto Matías, Manuel. Universidad Complutense de Madrid; España
Materia
Bioinformatics
Heterogeneous Computing
Hpc
Intel Xeon Phi
Power Consumption
Smith-Waterman
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/53930
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/53930
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architecturesRucci, EnzoGarcía, CarlosBotella, Guillermode Giusti, Armando EduardoNaiouf, Ricardo MarceloPrieto Matías, ManuelBioinformaticsHeterogeneous ComputingHpcIntel Xeon PhiPower ConsumptionSmith-Watermanhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Summary Alignment is essential in many areas such as biological, chemical and criminal forensics. The well-known Smith-Waterman (SW) algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. There are several implementations that take advantage of computing parallelization, such as manycores, FPGAS or GPUS, in order to reduce the alignment effort. In this research, we adapt, develop and tune the SW algorithm named SWIMM on a heterogeneous platform based on Intel's Xeon and Xeon Phi coprocessor. SWIMM is a free tool available in a public git repository https://github.com/enzorucci/SWIMM. We efficiently exploit data and thread-level parallelism, reaching up to 380 GCUPS on heterogeneous architecture, 350 GCUPS for the isolated Xeon and 50 GCUPS on Xeon Phi. Despite the heterogeneous implementation obtaining the best performance, it is also the most energy-demanding. In fact, we also present a trade-off analysis between performance and power consumption. The greenest configuration is based on an isolated multicore system that exploits AVX2 instruction set architecture reaching 1.5 GCUPS/Watts.Fil: Rucci, Enzo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; ArgentinaFil: García, Carlos. Universidad Complutense de Madrid; EspañaFil: Botella, Guillermo. Universidad Complutense de Madrid; EspañaFil: de Giusti, Armando Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; ArgentinaFil: Naiouf, Ricardo Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; ArgentinaFil: Prieto Matías, Manuel. Universidad Complutense de Madrid; EspañaJohn Wiley & Sons Ltd2015-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/53930Rucci, Enzo; García, Carlos; Botella, Guillermo; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; et al.; An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures; John Wiley & Sons Ltd; Concurrency and Computation: Practice and Experience; 27; 18; 12-2015; 5517-55371532-0626CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/cpe.3598info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.3598info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:26:19Zoai:ri.conicet.gov.ar:11336/53930instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:26:19.957CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
title An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
spellingShingle An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
Rucci, Enzo
Bioinformatics
Heterogeneous Computing
Hpc
Intel Xeon Phi
Power Consumption
Smith-Waterman
title_short An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
title_full An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
title_fullStr An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
title_full_unstemmed An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
title_sort An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures
dc.creator.none.fl_str_mv Rucci, Enzo
García, Carlos
Botella, Guillermo
de Giusti, Armando Eduardo
Naiouf, Ricardo Marcelo
Prieto Matías, Manuel
author Rucci, Enzo
author_facet Rucci, Enzo
García, Carlos
Botella, Guillermo
de Giusti, Armando Eduardo
Naiouf, Ricardo Marcelo
Prieto Matías, Manuel
author_role author
author2 García, Carlos
Botella, Guillermo
de Giusti, Armando Eduardo
Naiouf, Ricardo Marcelo
Prieto Matías, Manuel
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Bioinformatics
Heterogeneous Computing
Hpc
Intel Xeon Phi
Power Consumption
Smith-Waterman
topic Bioinformatics
Heterogeneous Computing
Hpc
Intel Xeon Phi
Power Consumption
Smith-Waterman
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Summary Alignment is essential in many areas such as biological, chemical and criminal forensics. The well-known Smith-Waterman (SW) algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. There are several implementations that take advantage of computing parallelization, such as manycores, FPGAS or GPUS, in order to reduce the alignment effort. In this research, we adapt, develop and tune the SW algorithm named SWIMM on a heterogeneous platform based on Intel's Xeon and Xeon Phi coprocessor. SWIMM is a free tool available in a public git repository https://github.com/enzorucci/SWIMM. We efficiently exploit data and thread-level parallelism, reaching up to 380 GCUPS on heterogeneous architecture, 350 GCUPS for the isolated Xeon and 50 GCUPS on Xeon Phi. Despite the heterogeneous implementation obtaining the best performance, it is also the most energy-demanding. In fact, we also present a trade-off analysis between performance and power consumption. The greenest configuration is based on an isolated multicore system that exploits AVX2 instruction set architecture reaching 1.5 GCUPS/Watts.
Fil: Rucci, Enzo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: García, Carlos. Universidad Complutense de Madrid; España
Fil: Botella, Guillermo. Universidad Complutense de Madrid; España
Fil: de Giusti, Armando Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: Naiouf, Ricardo Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de la Plata. Facultad de Informatica. Instituto de Investigación En Informatica Lidi; Argentina
Fil: Prieto Matías, Manuel. Universidad Complutense de Madrid; España
description Summary Alignment is essential in many areas such as biological, chemical and criminal forensics. The well-known Smith-Waterman (SW) algorithm is able to retrieve the optimal local alignment with quadratic time and space complexity. There are several implementations that take advantage of computing parallelization, such as manycores, FPGAS or GPUS, in order to reduce the alignment effort. In this research, we adapt, develop and tune the SW algorithm named SWIMM on a heterogeneous platform based on Intel's Xeon and Xeon Phi coprocessor. SWIMM is a free tool available in a public git repository https://github.com/enzorucci/SWIMM. We efficiently exploit data and thread-level parallelism, reaching up to 380 GCUPS on heterogeneous architecture, 350 GCUPS for the isolated Xeon and 50 GCUPS on Xeon Phi. Despite the heterogeneous implementation obtaining the best performance, it is also the most energy-demanding. In fact, we also present a trade-off analysis between performance and power consumption. The greenest configuration is based on an isolated multicore system that exploits AVX2 instruction set architecture reaching 1.5 GCUPS/Watts.
publishDate 2015
dc.date.none.fl_str_mv 2015-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/53930
Rucci, Enzo; García, Carlos; Botella, Guillermo; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; et al.; An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures; John Wiley & Sons Ltd; Concurrency and Computation: Practice and Experience; 27; 18; 12-2015; 5517-5537
1532-0626
CONICET Digital
CONICET
url http://hdl.handle.net/11336/53930
identifier_str_mv Rucci, Enzo; García, Carlos; Botella, Guillermo; de Giusti, Armando Eduardo; Naiouf, Ricardo Marcelo; et al.; An energy-aware performance analysis of SWIMM: Smith-Waterman implementation on Intel's Multicore and Manycore architectures; John Wiley & Sons Ltd; Concurrency and Computation: Practice and Experience; 27; 18; 12-2015; 5517-5537
1532-0626
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/cpe.3598
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.3598
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Ltd
publisher.none.fl_str_mv John Wiley & Sons Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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