The focus of Bioinformatics research is usually on two aspects—genomics and proteomics, specifically, it’s starting from nucleic acid and protein sequences, analyzing the structural and functional biological information expressed in the sequences. Biological sequence alignment is one of the common problems, the Needleman-Wunsch algorithm based on dynamic programming is the most basic algorithm, and Edit Distance(Levenshtein Distance) algorithm is also widely used in DNA sequence alignment. Nowadays, there are large amount of improvements on the Needleman-Wunsch algorithm, while few on Edit Distance algorithm, so this paper focuses on revealing the effects of parallel design on optimizing the Edit Distance algorithm, and it also compares the two algorithms’ different significances in DNA sequence alignment objectively.