Skip to Main Content
Bayesian phylogenetic inference is an important alternative to maximum likelihood-based phylogenetic method. However, inferring large trees using the Bayesian approach is computationally demanding - requiring huge amounts of memory and months of computational time. With a combination of novel parallel algorithms and latest system technology, terascale phylogenetic tools provide biologists the computational power necessary to conduct experiments on very large dataset, and thus aid construction of the tree of life. In this work we evaluate the performance of PBPI, a parallel application that reconstructs phylogenetic trees using MCMC-based Bayesian methods, on two terascale systems, Blue Gene/L at IBM Rochester and System X at Virginia Tech. Our results confirm that for a benchmark dataset with 218 taxa and 10000 characters, PBPI can achieve linear speedup on 1024 or more processors for both systems.