Due to the continuous explosive accumulation of sequence data, which is driven by novel sequencing techniques such as, e.g., pyrosequencing, the application of high performance computing techniques will become crucial to the success of Evolutionary Bioinformatics. In addition, emerging parallel multi - and many-core computer architectures pose new challenges for the field, since a large number of widely used applications will have to be ported to these systems.
I will outline how the application of high performance computing methods can contribute to solve challenging problems such as large-scale phylogenetic inference under the Maximum Likelihood criterion, phylogenetic classification of query sequences, and co-phylogenetic analyses based on statistical models. Within this context I will review current algorithmic and computational problems in evolutionary Bioinformatics and address programming and performance issues ranging from small 8-core architectures up to the SGI Altix 4700 and the IBM BlueGene supercomputer.
I will conclude with an overview of current and future challenges.