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Comparative Study of the Parallelization of the Smith-Waterman Algorithm on OpenMP and Cuda C

机译:Smith沃特曼算法在OpenMP和Cuda C上并行化的比较研究

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In this paper, we present parallel programming approaches to calculate the values of the cells in matrix’s scoring used in the Smith-Waterman’s algorithm for sequence alignment. This algorithm, well known in bioinformatics for its applications, is unfortunately time-consuming on a serial computer. We use formulation based on anti-diagonals structure of data. This representation focuses on parallelizable parts of the algorithm without changing the initial formulation of the algorithm. Approaching data in that way give us a formulation more flexible. To examine this approach, we encode it in OpenMP and Cuda C. The performance obtained shows the interest of our paper.
机译:在本文中,我们提出了并行编程方法来计算Smith-Waterman序列比对算法中矩阵评分中单元格的值。不幸的是,这种算法在生物信息学中因其应用而闻名,但不幸的是,它在串行计算机上非常耗时。我们使用基于反对角线结构的数据公式。这种表示方式着重于算法的可并行化部分,而不改变算法的初始形式。以这种方式处理数据使我们的表述更加灵活。为了检验这种方法,我们在OpenMP和Cuda C中对其进行了编码。获得的性能表明了本文的兴趣。

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