| GPU加速的生物序列比对 |
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| 引用本文： | 林江,唐敏,童若锋.GPU加速的生物序列比对[J].计算机辅助设计与图形学学报,2010,22(3). |
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| 作者姓名： | 林江 唐敏 童若锋 |
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| 作者单位： | 浙江大学计算机科学与技术学院,杭州,310027 |
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| 基金项目： | 国家自然科学基金(60803054) |
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| 摘 要： | 为了精确高效地进行生物序列比对,提出一种GPU加速的Smith-Waterman算法.该算法使用菱形数据布局以更充分地利用GPU的并行处理能力;使用查询串分批处理技术来支持上百兆规模的序列比对;同时引入树形算法,以优化最大匹配值的计算.将该算法在一块NVIDIA GeForce GTX285显卡上实现,并使用多组不同规模的生物序列进行了比对实验.实验结果表明,与CPU上的串行算法相比,采用文中算法最高可获得120倍以上的性能提升.
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| 关 键 词： | Smith-Waterman算法 序列比对 CUDA |
GPU Accelerated Biological Sequence Alignment |
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| Lin Jiang,Tang Min, Tong Ruofeng.GPU Accelerated Biological Sequence Alignment[J].Journal of Computer-Aided Design & Computer Graphics,2010,22(3). |
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| Authors: | Lin Jiang Tang Min Tong Ruofeng |
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| Affiliation: | College of Computer Science and Technology/a>;Zhejiang University/a>;Hangzhou 310027 |
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| Abstract: | To improve the biological sequence alignment in accuracy and efficiency,a GPU accelerated Smith-Waterman algorithm is proposed.The algorithm uses diamond-shaped data layout to fully utilize the parallel processing capability of commodity GPUs.With a batched query technique,biological sequences with hundreds of millions units can be processed.The maximum match score computation is optimized with tree-based reduction.The algorithm has been implemented on an NVIDIA GeForce GTX 285 GPU,and tested with multiple ... |
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| Keywords: | Smith-Waterman algorithm sequence alignment CUDA |
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