Exploring FPGAs for accelerating the phylogenetic likelihood function

Driven by novel biological wet lab techniques such as pyrosequencing there has been an unprecedented molecular data explosion over the last 2-3 years. The growth of biological sequence data has significantly out-paced Moore’s law. This development also poses new computational and architectural challenges for the field of phylogenetic inference, i.e., the reconstruction of evolutionary histories (trees) for a set of organisms which are represented by respective molecular sequences. Phylogenetic trees are currently increasingly reconstructed from multiple genes or even whole genomes. The recently introduced term “phylogenomics” reflects this development. Hence, there is an urgent need to deploy and develop new techniques and computational solutions to calculate the computationally intensive scoring functions for phylogenetic trees. In this paper, we propose a dedicated computer architecture to compute the phylogenetic Maximum Likelihood (ML) function. The ML criterion represent...

• Type: Conference
• Year: 2009
• Where: IPPS
• Authors: Nikolaos Alachiotis, Euripides Sotiriades, Apostolos Dollas, Alexandros Stamatakis
• Keywords: Distributed And Parallel Computing, IPPS 2009, Phylogenetic, Phylogenetic Inference, Phylogenetic Trees