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Multi-GPU Approach for Large-Scale Multiple Sequence Alignment

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Siqueira, Rodrigo A. de O. ; Stefanes, Marco A. ; Rozante, Luiz C. S. ; Martins-Jr, David C. ; de Souza, Jorge E. S. ; Araujo, Eloi ; Gervasi, O ; Murgante, B ; Misra, S ; Garau, C ; Blecic, I ; Taniar, D ; Apduhan, BO ; Rocha, AMAC ; Tarantino, E ; Torre, CM
Número total de Autores: 16
Tipo de documento: Artigo Científico
Fonte: COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT I; v. 12949, p. 16-pg., 2021-01-01.
Resumo

Multiple sequence alignment is an important tool to represent similarities among biological sequences and it allows obtaining relevant information such as evolutionary history, among others. Due to its importance, several methods have been proposed to the problem. However, the inherent complexity of the problem allows only non-exact solutions and further for small length sequences or few sequences. Hence, the scenario of rapid increment of the sequence databases leads to prohibitive runtimes for large-scale sequence datasets. In this work we describe a Multi-GPU approach for the three stages of the Progressive Alignment method which allow to address a large number of lengthy sequence alignments in reasonable time. We compare our results with two popular aligners ClustalW-MPI and Clustal Omega and with CUDA NW module of the Rodinia Suite. Our proposal with 8 GPUs achieved speedups ranging from 28.5 to 282.6 with regard to ClustalW-MPI with 32 CPUs considering NCBI and synthetic datasets. When compared to Clustal Omega with 32 CPUs for NCBI and synthetic datasets we had speedups between 3.3 and 32. In comparison with CUDA NW_Rodinia the speedups range from 155 to 830 considering all scenarios. (AU)

Processo FAPESP: 18/21934-5 - Estatística de redes: teoria, métodos e aplicações
Beneficiário:André Fujita
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 18/18560-6 - Integração de dados para busca de marcadores biológicos de transtornos do neurodesenvolvimento
Beneficiário:Helena Paula Brentani
Modalidade de apoio: Auxílio à Pesquisa - Temático