SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences

Autores
Rucci, Enzo; Garcia, Carlos; Botella, Guillermo; De Giusti, Armando Eduardo; Naiouf, Marcelo; Prieto-Matias, Manuel
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions between two DNA or protein sequences. However, it may become impracticable in some contexts due to its high computational demands. Consequently, the computer science community has focused on the use of modern parallel architectures such as Graphics Processing Units (GPUs), Xeon Phi accelerators and Field Programmable Gate Arrays (FGPAs) to speed up large-scale workloads. Results: This paper presents and evaluates SWIFOLD: a Smith-Waterman parallel Implementation on FPGA with OpenCL for Long DNA sequences. First, we evaluate its performance and resource usage for different kernel configurations. Next, we carry out a performance comparison between our tool and other state-of-the-art implementations considering three different datasets. SWIFOLD offers the best average performance for small and medium test sets, achieving a performance that is independent of input size and sequence similarity. In addition, SWIFOLD provides competitive performance rates in comparison with GPU-based implementations on the latest GPU generation for the large dataset. Conclusions: The results suggest that SWIFOLD can be a serious contender for accelerating the SW alignment of DNA sequences of unrestricted size in an affordable way reaching on average 125 GCUPS and almost a peak of 270 GCUPS.
Instituto de Investigación en Informática
Materia
Ciencias Informáticas
Biología
DNA
Smith-Waterman
OpenCL
High-performance computing
FPGA
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/107848
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequencesRucci, EnzoGarcia, CarlosBotella, GuillermoDe Giusti, Armando EduardoNaiouf, MarceloPrieto-Matias, ManuelCiencias InformáticasBiologíaDNASmith-WatermanOpenCLHigh-performance computingFPGABackground: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions between two DNA or protein sequences. However, it may become impracticable in some contexts due to its high computational demands. Consequently, the computer science community has focused on the use of modern parallel architectures such as Graphics Processing Units (GPUs), Xeon Phi accelerators and Field Programmable Gate Arrays (FGPAs) to speed up large-scale workloads. Results: This paper presents and evaluates SWIFOLD: a Smith-Waterman parallel Implementation on FPGA with OpenCL for Long DNA sequences. First, we evaluate its performance and resource usage for different kernel configurations. Next, we carry out a performance comparison between our tool and other state-of-the-art implementations considering three different datasets. SWIFOLD offers the best average performance for small and medium test sets, achieving a performance that is independent of input size and sequence similarity. In addition, SWIFOLD provides competitive performance rates in comparison with GPU-based implementations on the latest GPU generation for the large dataset. Conclusions: The results suggest that SWIFOLD can be a serious contender for accelerating the SW alignment of DNA sequences of unrestricted size in an affordable way reaching on average 125 GCUPS and almost a peak of 270 GCUPS.Instituto de Investigación en Informática2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/107848enginfo:eu-repo/semantics/altIdentifier/url/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6245597&blobtype=pdfinfo:eu-repo/semantics/altIdentifier/issn/1752-0509info:eu-repo/semantics/altIdentifier/pmid/30458766info:eu-repo/semantics/altIdentifier/doi/10.1186/s12918-018-0614-6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:15:46Zoai:sedici.unlp.edu.ar:10915/107848Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:15:46.668SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
title SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
spellingShingle SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
Rucci, Enzo
Ciencias Informáticas
Biología
DNA
Smith-Waterman
OpenCL
High-performance computing
FPGA
title_short SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
title_full SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
title_fullStr SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
title_full_unstemmed SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
title_sort SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences
dc.creator.none.fl_str_mv Rucci, Enzo
Garcia, Carlos
Botella, Guillermo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Prieto-Matias, Manuel
author Rucci, Enzo
author_facet Rucci, Enzo
Garcia, Carlos
Botella, Guillermo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Prieto-Matias, Manuel
author_role author
author2 Garcia, Carlos
Botella, Guillermo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Prieto-Matias, Manuel
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Biología
DNA
Smith-Waterman
OpenCL
High-performance computing
FPGA
topic Ciencias Informáticas
Biología
DNA
Smith-Waterman
OpenCL
High-performance computing
FPGA
dc.description.none.fl_txt_mv Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions between two DNA or protein sequences. However, it may become impracticable in some contexts due to its high computational demands. Consequently, the computer science community has focused on the use of modern parallel architectures such as Graphics Processing Units (GPUs), Xeon Phi accelerators and Field Programmable Gate Arrays (FGPAs) to speed up large-scale workloads. Results: This paper presents and evaluates SWIFOLD: a Smith-Waterman parallel Implementation on FPGA with OpenCL for Long DNA sequences. First, we evaluate its performance and resource usage for different kernel configurations. Next, we carry out a performance comparison between our tool and other state-of-the-art implementations considering three different datasets. SWIFOLD offers the best average performance for small and medium test sets, achieving a performance that is independent of input size and sequence similarity. In addition, SWIFOLD provides competitive performance rates in comparison with GPU-based implementations on the latest GPU generation for the large dataset. Conclusions: The results suggest that SWIFOLD can be a serious contender for accelerating the SW alignment of DNA sequences of unrestricted size in an affordable way reaching on average 125 GCUPS and almost a peak of 270 GCUPS.
Instituto de Investigación en Informática
description Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions between two DNA or protein sequences. However, it may become impracticable in some contexts due to its high computational demands. Consequently, the computer science community has focused on the use of modern parallel architectures such as Graphics Processing Units (GPUs), Xeon Phi accelerators and Field Programmable Gate Arrays (FGPAs) to speed up large-scale workloads. Results: This paper presents and evaluates SWIFOLD: a Smith-Waterman parallel Implementation on FPGA with OpenCL for Long DNA sequences. First, we evaluate its performance and resource usage for different kernel configurations. Next, we carry out a performance comparison between our tool and other state-of-the-art implementations considering three different datasets. SWIFOLD offers the best average performance for small and medium test sets, achieving a performance that is independent of input size and sequence similarity. In addition, SWIFOLD provides competitive performance rates in comparison with GPU-based implementations on the latest GPU generation for the large dataset. Conclusions: The results suggest that SWIFOLD can be a serious contender for accelerating the SW alignment of DNA sequences of unrestricted size in an affordable way reaching on average 125 GCUPS and almost a peak of 270 GCUPS.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/107848
url http://sedici.unlp.edu.ar/handle/10915/107848
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6245597&blobtype=pdf
info:eu-repo/semantics/altIdentifier/issn/1752-0509
info:eu-repo/semantics/altIdentifier/pmid/30458766
info:eu-repo/semantics/altIdentifier/doi/10.1186/s12918-018-0614-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 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)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
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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