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

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.