BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational…

• NS
  National Science Foundation

  Awards: EF-0905606, 1036448, 0949453, 0732920, 0331495, DEB-1036448, DMS-0931642, DBI-0755048, 0755048, 0905606, 0931642
• OS
  Ohio State University
• NE
  National Evolutionary Synthesis Center

  Awards: 0905606, EF-0905606
• WT
  Wellcome Trust
• NI
  National Institutes of Health

  Awards: GM086887, HG006139, NS063897, R01-NS063897
• DF
  Directorate for Biological Sciences

  Award: 0931642
• BA
  Biotechnology and Biological Sciences Research Council

  Awards: BB/H011285/1, BB/H011285/1