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Title: Irregular alignment of arbitrarily long DNA sequences on GPU
Authors: Esteban, Perez-Wohlfeil
Oswaldo, Trelles
Nicolás, Guil
Issue Date: 2022
Publisher: Springer
Abstract: The use of Graphics Processing Units to accelerate computational applications is increasingly being adopted due to its affordability, flexibility and performance. However, achieving top performance comes at the price of restricted data-parallelism models. In the case of sequence alignment, most GPU-based approaches focus on accelerating the Smith-Waterman dynamic programming algorithm due to its regularity. Nevertheless, because of its quadratic complexity, it becomes impractical when comparing long sequences, and therefore heuristic methods are required to reduce the search space.
Description: CC BY
URI: https://link.springer.com/article/10.1007/s11227-022-05007-z
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8276
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