Abstract
Sequence analysis has become essential to the study of genomes and biological research in general. Basic Local Alignment Search Tool (BLAST) leads the way as the most accepted method for performing necessary query searches and analysis of discovered genes. Combating growing data sizes, with the goal of speeding up job runtimes, scientist are resorting to grid computing technologies. However, grid environments are characterized by dynamic, heterogeneous, and transient state of available resources causing major hindrance to users when trying to realize user-desired levels of service. This paper analyzes performance characteristics of NCBI BLAST on several resources and captures influence of resource characteristics and job parameters on BLAST job runtime across those resources. Obtained results are summarized as a set of principles characterizing performance of NCBI BLAST across homogeneous and heterogeneous environments. These principles are then applied and verified through creation of a grid-enabled BLAST wrapper application called Dynamic BLAST. Results show runtime savings up to 50% and resource utilization improvement of approximately 40%.
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