Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU

Autores
Vidal, Pablo Javier; Olivera, Ana Carolina
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The Deoxyribonucleic Acid Fragment Assembly Problem (DNA-FAP) consists in reconstructing a DNA chain from a set of fragments taken randomly. This problem represents an important step in the genome project. Several authors are proposed different approaches to solve the DNA-FAP. In particular, nature-inspired algorithms have been used for its resolution. Even they were obtaining good results; its computational time associated is high. The bio-inspired algorithms are iterative search processes that can explore and exploit efficiently the solution space. Firefly Algorithm is one of the recent evolutionary computing models which is inspired by the flashing light behaviour of fireflies. Recently, the Graphics Processing Units (GPUs) technology are emerge as a novel environment for a parallel implementation and execution of bio-inspired algorithms. Therefore, the use of GPU-based parallel computing it is possible as a complementary tool to speed-up the search. In this work, we design and implement a Discrete Firefly Algorithm (DFA) on a GPU architecture in order to speed-up the search process for solving the DNA Fragment Assembly Problem. Through several experiments, the efficiency of the algorithm and the quality of the results are demonstrated with the potential to applied for longer sequences or sequences of unknown length as well.
Fil: Vidal, Pablo Javier. Universidad Nacional de la Patagonia Austral. Unidad Académica Caleta Olivia. Departamento de Ciencias Exactas y Naturales; Argentina. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; Argentina
Fil: Olivera, Ana Carolina. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; Argentina. Universidad Nacional de la Patagonia Austral. Unidad Académica Caleta Olivia. Departamento de Ciencias Exactas y Naturales; Argentina
Materia
DNA FRAGMENT ASSEMBLY PROBLEM
GRAPHIC PROCESSING UNITS
PARALLELISM
FIREFLY ALGORITHM
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/102302
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/102302
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPUVidal, Pablo JavierOlivera, Ana CarolinaDNA FRAGMENT ASSEMBLY PROBLEMGRAPHIC PROCESSING UNITSPARALLELISMFIREFLY ALGORITHMhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The Deoxyribonucleic Acid Fragment Assembly Problem (DNA-FAP) consists in reconstructing a DNA chain from a set of fragments taken randomly. This problem represents an important step in the genome project. Several authors are proposed different approaches to solve the DNA-FAP. In particular, nature-inspired algorithms have been used for its resolution. Even they were obtaining good results; its computational time associated is high. The bio-inspired algorithms are iterative search processes that can explore and exploit efficiently the solution space. Firefly Algorithm is one of the recent evolutionary computing models which is inspired by the flashing light behaviour of fireflies. Recently, the Graphics Processing Units (GPUs) technology are emerge as a novel environment for a parallel implementation and execution of bio-inspired algorithms. Therefore, the use of GPU-based parallel computing it is possible as a complementary tool to speed-up the search. In this work, we design and implement a Discrete Firefly Algorithm (DFA) on a GPU architecture in order to speed-up the search process for solving the DNA Fragment Assembly Problem. Through several experiments, the efficiency of the algorithm and the quality of the results are demonstrated with the potential to applied for longer sequences or sequences of unknown length as well.Fil: Vidal, Pablo Javier. Universidad Nacional de la Patagonia Austral. Unidad Académica Caleta Olivia. Departamento de Ciencias Exactas y Naturales; Argentina. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; ArgentinaFil: Olivera, Ana Carolina. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; Argentina. Universidad Nacional de la Patagonia Austral. Unidad Académica Caleta Olivia. Departamento de Ciencias Exactas y Naturales; ArgentinaComsis Consortium2018-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/102302Vidal, Pablo Javier; Olivera, Ana Carolina; Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU; Comsis Consortium; Computer Science And Information Systems; 15; 2; 7-2018; 273-2931820-0214CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.doiserbia.nb.rs/Article.aspx?ID=1820-02141800009Vinfo:eu-repo/semantics/altIdentifier/doi/10.2298/CSIS170510009Vinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:10:26Zoai:ri.conicet.gov.ar:11336/102302instacron: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 10:10:27.232CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
title Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
spellingShingle Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
Vidal, Pablo Javier
DNA FRAGMENT ASSEMBLY PROBLEM
GRAPHIC PROCESSING UNITS
PARALLELISM
FIREFLY ALGORITHM
title_short Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
title_full Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
title_fullStr Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
title_full_unstemmed Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
title_sort Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU
dc.creator.none.fl_str_mv Vidal, Pablo Javier
Olivera, Ana Carolina
author Vidal, Pablo Javier
author_facet Vidal, Pablo Javier
Olivera, Ana Carolina
author_role author
author2 Olivera, Ana Carolina
author2_role author
dc.subject.none.fl_str_mv DNA FRAGMENT ASSEMBLY PROBLEM
GRAPHIC PROCESSING UNITS
PARALLELISM
FIREFLY ALGORITHM
topic DNA FRAGMENT ASSEMBLY PROBLEM
GRAPHIC PROCESSING UNITS
PARALLELISM
FIREFLY ALGORITHM
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The Deoxyribonucleic Acid Fragment Assembly Problem (DNA-FAP) consists in reconstructing a DNA chain from a set of fragments taken randomly. This problem represents an important step in the genome project. Several authors are proposed different approaches to solve the DNA-FAP. In particular, nature-inspired algorithms have been used for its resolution. Even they were obtaining good results; its computational time associated is high. The bio-inspired algorithms are iterative search processes that can explore and exploit efficiently the solution space. Firefly Algorithm is one of the recent evolutionary computing models which is inspired by the flashing light behaviour of fireflies. Recently, the Graphics Processing Units (GPUs) technology are emerge as a novel environment for a parallel implementation and execution of bio-inspired algorithms. Therefore, the use of GPU-based parallel computing it is possible as a complementary tool to speed-up the search. In this work, we design and implement a Discrete Firefly Algorithm (DFA) on a GPU architecture in order to speed-up the search process for solving the DNA Fragment Assembly Problem. Through several experiments, the efficiency of the algorithm and the quality of the results are demonstrated with the potential to applied for longer sequences or sequences of unknown length as well.
Fil: Vidal, Pablo Javier. Universidad Nacional de la Patagonia Austral. Unidad Académica Caleta Olivia. Departamento de Ciencias Exactas y Naturales; Argentina. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; Argentina
Fil: Olivera, Ana Carolina. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; Argentina. Universidad Nacional de la Patagonia Austral. Unidad Académica Caleta Olivia. Departamento de Ciencias Exactas y Naturales; Argentina
description The Deoxyribonucleic Acid Fragment Assembly Problem (DNA-FAP) consists in reconstructing a DNA chain from a set of fragments taken randomly. This problem represents an important step in the genome project. Several authors are proposed different approaches to solve the DNA-FAP. In particular, nature-inspired algorithms have been used for its resolution. Even they were obtaining good results; its computational time associated is high. The bio-inspired algorithms are iterative search processes that can explore and exploit efficiently the solution space. Firefly Algorithm is one of the recent evolutionary computing models which is inspired by the flashing light behaviour of fireflies. Recently, the Graphics Processing Units (GPUs) technology are emerge as a novel environment for a parallel implementation and execution of bio-inspired algorithms. Therefore, the use of GPU-based parallel computing it is possible as a complementary tool to speed-up the search. In this work, we design and implement a Discrete Firefly Algorithm (DFA) on a GPU architecture in order to speed-up the search process for solving the DNA Fragment Assembly Problem. Through several experiments, the efficiency of the algorithm and the quality of the results are demonstrated with the potential to applied for longer sequences or sequences of unknown length as well.
publishDate 2018
dc.date.none.fl_str_mv 2018-07
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/11336/102302
Vidal, Pablo Javier; Olivera, Ana Carolina; Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU; Comsis Consortium; Computer Science And Information Systems; 15; 2; 7-2018; 273-293
1820-0214
CONICET Digital
CONICET
url http://hdl.handle.net/11336/102302
identifier_str_mv Vidal, Pablo Javier; Olivera, Ana Carolina; Solving the DNA fragment assembly problem with a parallel discrete firefly algorithm implemented on GPU; Comsis Consortium; Computer Science And Information Systems; 15; 2; 7-2018; 273-293
1820-0214
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.doiserbia.nb.rs/Article.aspx?ID=1820-02141800009V
info:eu-repo/semantics/altIdentifier/doi/10.2298/CSIS170510009V
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Comsis Consortium
publisher.none.fl_str_mv Comsis Consortium
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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