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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/107848
Ver los metadatos del registro completo
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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:UNLP2025-09-29T11:23:51Zoai: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:13292025-09-29 11:23:52.068SEDICI (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 |
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http://sedici.unlp.edu.ar/handle/10915/107848 |
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eng |
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eng |
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