An Optimized Reconfigurable System for Computing the Phylogenetic Likelihood Function on DNA Data

The Phylogenetic Likelihood Function (PLF) is an important statistical function for evaluating phylogenetic trees. To this end, the PLF is the computational kernel of all state-of-the-art likelihood-based phylogenetic inference programs. Typically, it accounts for more than 85% of total execution time in such programs. We present a substantially improved hardware architecture for computing the PLF based on previous experiences with implementing the PLF on reconfigurable logic. Our new design is optimized for computing the PLF on four-state (DNA) input data. It is also adapted to the computational requirements of real-world tree inference programs and completely independent of the specific tree search algorithm at hand. Furthermore, we describe how our architecture can be modified and adapted to handle general n-state data, such as protein (20 states) or RNA secondary structure data (6, 7, or 16 states, depending on the model). Finally, we designed an interface mechanism such that our PLF hardware architecture can interact with the widely-used phylogenetic inference tool RAxML. We deploy FPGA technology to verify the correctness of the architecture and to evaluate performance.