Abstract
Abstract Decoding the human genome in the past decades has brought into focus a computationally intensive operation through DNA profiling. The typical search space for these kinds of problems is extremely large and requires specialized hardware and algorithms to perform the necessary sequence analysis. In this paper, we propose an innovative and scalable approach to exact multi-pattern matching of nucleotide sequences by harnessing the massively parallel computing power found in commodity graphical processing units. Our approach places careful consideration on preprocessing of DNA datasets and runtime performance, while exploiting the full capabilities of the heterogeneous platform it runs on. Finally, we evaluate our models against real-world DNA sequences.
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