Efficient Three-Way Needleman-Wunsch Algorithm by Diagonal Computations on GPU
碩士 === 長庚大學 === 資訊工程學系 === 98 === Three-way alignment can be solved sequentially in O(mnl) time complexity and O(mn) space complexity, where m, n and l are the lengths of the sequences to be aligned. The complexities of three-way alignment limit its applicability CUDA (an acronym for Compute Un...
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| Format: | Others |
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2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/10867372806426828009 |
| Summary: | 碩士 === 長庚大學 === 資訊工程學系 === 98 === Three-way alignment can be solved sequentially in O(mnl) time complexity and O(mn) space complexity, where m, n and l are the lengths of the sequences to be aligned. The complexities of three-way alignment limit its applicability
CUDA (an acronym for Compute Unified Device Architecture) is a parallel computing architecture developed by NVIDIA. CUDA is the computing engine in NVIDIA graphics processing units (GPUs) that is accessible to software developers through variants of industry standard programming languages. Programmers can use C programming for CUDA. Three-way Needleman-Wunsch algorithm on CPU is a time-consuming problem. It needs very much time to calculate the results. So we try to design an efficient three-way Needleman-Wunsch algorithm by diagonal computations on GPU.
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