GPU computing for the tree of life

by Daniel Ayres (Center for Bioinformatics and Computational Biology, University of Maryland)

Wednesday 9 Sept 2009, 16:00 → 17:00 Europe/Stockholm

RB35 (RB35)

With the rapid advances in the collection of DNA sequence data, the limitation for biological understanding of these data has increasingly become a computational problem. This is especially true for the accurate determination of phylogenetic relationships, where likelihood calculation is the main bottleneck. Meanwhile, general-purpose computing on graphics processing units (GPUs) has quickly become an important area of research, and scientific computing applications in several areas have seen notable performance speedups from adaptation to this hardware.

I will present BEAGLE, an open API and fast GPU implementations of a library for evaluating phylogenetic likelihoods of biomolecular sequence evolution. BEAGLE uses novel algorithms and methods for evaluating phylogenies under arbitrary molecular evolutionary models on GPUs, making use of the large number of processing cores to efficiently parallelize calculations even for large state-size models. The objective is to provide high performance evaluation 'services' to a wide range of phylogenetic software, both Bayesian samplers and Maximum Likelihood optimizers. Current results show a near 90-fold speed increase over an optimized CPU-based computation for estimating the phylogeny of 62 complete mitochondrial genomes of carnivores under a 60-state codon model.