high performance computing on graphics processing units: hgpu.org

This paper provides a novel framework for accelerating the solution of the pairwise DNA sequence alignment problem using CUDA parallel paradigm available on the NVIDIA GPU. The main idea is to implement a new algorithm that assigns different nucleotide weights using GPU architectures then merge the subsequences of match using CPU to get the optimum local alignment. The paper describes both the algorithm and the implementation of it using both the GPU and CPU to constitute a hybrid model for solving DNA sequence alignment problem on DNA molecules. Experimental results demonstrate a considerable reduction in run time relative to traditional Smith-Waterman implementation on traditional processors.