High-Performance Computing of BEAST/BEAGLE in Bayesian Phylogenetics using SDumont Hybrid Resources

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


Bayesian phylogenetic algorithms are computationally intensive. BEAST 1.10 inferences made use of the BEAGLE 3 high-performance library for efficient likelihood computations. The strategy allows phylogenetic inference and dating in current knowledge for SARS-CoV-2 transmission. Follow-up simulations on hybrid resources of Santos Dumont supercomputer using four phylogenomic data sets, we characterize the scaling performance behavior of BEAST 1.10. Our results provide insight into the species tree and MCMC chain length estimation, identifying preferable requirements to improve the use of high-performance computing resources. Ongoing steps involve analyzes of SARS-CoV-2 using BEAST 1.8 in multi-GPUs.

Palavras-chave: High-Performance Computing, Computational Molecular Evolution, Bayesian Phylogenetic Analysis


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OCAÑA, Kary; COELHO, Micaella ; FREIRE, Guilherme; OSTHOFF, Carla. High-Performance Computing of BEAST/BEAGLE in Bayesian Phylogenetics using SDumont Hybrid Resources. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 14. , 2020, Cuiabá. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 121-128. ISSN 2763-8774. DOI: https://doi.org/10.5753/bresci.2020.11190.