Exploração de Módulos Paralelo Híıbrido de Bioinformática para Ambientes GPU de Supercomputação

• Guilherme Freire FAETERJ / LNCC
• Kary Ocaña LNCC
• Micaella Coelho LNCC
• Carla Osthoff LNCC

DOI: https://doi.org/10.5753/eradrj.2020.14521

Abstract

Bayesian phylogenetic algorithms are computationally intensive. BEAST Bayesian software coupled to BEAGLE 3 high-performance library had been tested on the hybrid resources of the Santos Dumont supercomputer. For analysing large Dengue virus data sets, the use of one or more GPUs proved more efficient than using multi-core.

Keywords: Arquiteturas Dedicadas e Específicas (GPUs, FPGAs, e outras), Aplicações em Agricultura, Biologia, Engenharia, Física, Matemática, Medicina, Mercado Financeiro, Nanociências, Óleo e Gás, Química e outras áreas

References

Jin, Z. and Bakos, J. D. (2013). Extending the beagle library to a multi fpga platform. BMC Bioinformatics, 14(1):25.

Ocaña, K., Coelho, M., Freire, G., and Osthoff, C. (2020). High-performance computing of beast/beagle in bayesian phylogenetics using sdumont hybrid resources. In 14o BreSci – Brazilian e-Science Workshop. (Aceito em processo de publicação).

Yin, Z., Lan, H., Tan, G., Lu, M., Vasilakos, A. V., and Liu, W. (2017). Computing platforms for big biological data analytics: Perspectives and challenges. Computational and Structural Biotechnology Journal, 15:403–411.