I/O Induced Scalability Limits of Bioinformatics Applications

The growing size of sequence, protein and other biological databases results in an increased computational complexity of the analysis process. Often parallelization is the only solution to limit the turnaround time within reasonable limits. Most scalability studies focus on the parallel algorithm and the resulting communication and synchronization patterns of the implementations. In this paper we examine to what extend I/O bottlenecks limit the scalability on current and future architectures. We study the behavior of two different bioinformatics applications (THREADER, HMMER) and show that these applications are representatives of two different classes with distinct I/O profiles and demands.