High-Performance Computing for Statistical Phylogenetics
Statistical phylogenetic analyses based on maximum likelihood (ML) and Bayesian inference are computationally challenging because of the intensive nature of the calculations required. At the core of statistical phylogenetics is the calculation of the likelihood (probability) of the observed molecular sequence character states under a specific model of evolution using a recursive algorithm, and the computation of this calculation comprises most of the running time for analyses. Decreasing the time (wall clock) for this computation is the raison d’être for the BEAGLE library, a parallel computing platform for high-performance calculation of phylogenetic likelihoods that makes efficient use of the fine-scale parallelization capabilities of computer processors, especially graphics processing units (GPUs).
- National Science Foundation award to increase performance of BEAGLE library for SARS-CoV-2 genomic data
- BEAGLE 3: improved performance, scaling, and usability for a high-performance computing library for statistical phylogenetics
- Rerooting trees increases opportunities for concurrent computation and results in markedly improved performance for phylogenetic inference
- BEAGLE project wins NVIDIA Global Impact Award