Abstract
Multi-core and many-core architectures are widely adopted by researchers in applied sciences and engineering, owing to their reasonable cost, and ease of access. Moreover, their painless hardware set-up process and rather simple programming paradigm attract more researchers to acquire them and implement their time-expensive computations on these platforms. Planted Motif Search problem is one of the most challenging problems in bioinformatics whose goal is to enumerate all strings of length ℓ that are commonly planted in a given set of DNA sequences. In this paper, we propose an efficient method of thread parallelization to accelerate the latest Quorum Planted Motif Search algorithm (qPMS9) on multi-core and many-core systems. Our contribution towards dynamic scheduling of threads and parallelization of loops in the proposed method outperforms previous sequential and parallel algorithms.
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