Performance Evaluation of Fast Smith-Waterman Algorithm for Sequence Database Searches Using CUDA GPU-Based Parallel Computing

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Provided by: AICIT
Topic: Hardware
Format: PDF
In bioinformatics, one of the gold-standard algorithms to compute the optimal similarity score between sequences in a sequence database searches is Smith-Waterman algorithm that uses dynamic programming. This algorithm has a quadratic time complexity which requires a long computation time for large-sized data. In this issue, parallel computing is essential for sequence database searches in order to reduce the running time and to increase the performance. In this paper, the authors discuss the parallel implementation performance of Smith-Waterman algorithm in GPU using CUDA C programming language with NVCC compiler on Linux environment.
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