利用GPGPU 搭配CUDA語言平行化加速生物演算法Smith-Waterman的序列比對

In bioinformatics, we often have to search for the similarity of the two sequences to identify similar fragments of two sequences. For more advanced technology &information progress, the number of sequence accumulated in the databases increases rapidly in order to solve a large number of searching. So there are a lot of search algorithms & tools had been suggested, such as Smith-Waterman, BLAST …, etc. Due to the size of database growing, the search time increase and could not completed search job within a requested time. How to find a better algorithm to accelerate the search speed is what we’re looking for. The GPGPU( General Purpose GPU), own a lot of SP(Streaming Processor) , is very suitable for large computing requirements. Under the specific support of particular language CUDA, GUGPU can fully perform well. In this paper we use the GPGPU as the parallel computing platform. We present a parallel method of calculation and also provide the way of optimization of memory to improve the efficiency of Smith-Waterman search algorithm. It makes us reduce the execution time to achieve a better efficiency.