WFA-FPGA: An efficient accelerator of the wavefront algorithm for short and long read genomics alignment
In the last years, advances in genome sequencing technologies have enabled the proliferation of genomic applications that guide personalized medicine. These applications have an enormous computational cost due to the large amount of genomic data they process. The first step in many of these applicat...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/401697 |
| Acceso en línea: | https://hdl.handle.net/2117/401697 https://dx.doi.org/10.1016/j.future.2023.07.008 |
| Access Level: | acceso abierto |
| Palabra clave: | Genomics Field programmable gate arrays Energy consumption Acceleration Read alignment FPGA Co-design WFA Genòmica Matrius de portes programables per l'usuari Energia -- Consum Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| Sumario: | In the last years, advances in genome sequencing technologies have enabled the proliferation of genomic applications that guide personalized medicine. These applications have an enormous computational cost due to the large amount of genomic data they process. The first step in many of these applications consists in aligning DNA reads against a reference genome. Very recently, the wavefront alignment (WFA) algorithm has been introduced, significantly reducing the execution time of the read alignment process. This paper presents the first FPGA-based hardware/software co-designed accelerator of such relevant algorithm. Compared to the reference WFA CPU-only implementation, the proposed accelerator achieves performance speedups of up to 13.5 while consuming up to 14.6 less energy when aligning short reads. When aligning long reads, the proposed accelerator achieves speedups of up to 9.9 while consuming up to 10.9 less energy. |
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