COMPETENCE NETWORK FOR TECHNICAL, SCIENTIFIC HIGH PERFORMANCE COMPUTING IN BAVARIA
Field of work:KONWIHR Division South
High Performance Computing & Emerging Parallel Architectures for Evolutionary Bioinformatics
The Maximum Likelihood (ML) criterion for phylogenetic (evolutionary) infe- rence has repeatedly been shown to be one of the most accurate models for phylogeny reconstruction. Recent advances in search algorithms and high-performance computing have lead to a new generation of programs for ML-based phylogenetic inference that scale well up to several thousand sequences. However, due to the continuously accelerating accumulation of sequence data that is driven by novel wet-lab techniques such as pyrosequencing, the algorithmic and technical development can hardly keep pace with the forthcoming data flood. The main goal of this project will be to devise and implement novel parallelization strategies as well as to assess emerging parallel HW architectures and programming paradigms for large-scale phylogeny reconstruction. Apart from the development of proof-of-concept parallelizations and system-level mechanisms to facilitate parallelization, particular emphasis will be put on developing fully usable and accessible open-source Bioinformatics tools for production-level runs, i.e., tools that will contribute to generate novel Biological and medical insights. Therefore, another important part of this project will focus on joint interdisciplinary large-scale real-world phylogenetic analyses on the HLRB II and an IBM BlueGene/L system located at the San Diego Supercomputer Center in collaboration with Biologists.