Biological sequence alignment is an important issue in the field of bioinformatics, and the rationality and correctness of alignment results are crucial to the researches based on sequence alignment. It is of great significance to exploit the computational potential with the help of parallel computing to improve alignment efficiency under the premise of ensuring alignment correctness. We propose a parallel alignment scheme based on the ant colony algorithm for the global sequences alignment problem. Aiming at the two most time-consuming steps in the ant colony algorithm, the search of comparison path and the pheromone update, we present a parallel method based on the shared memory model. Experiments on Tianhe II by the OpenMP show that with eight threads in parallel, the speedup can achieve 503, and the longer the sequence is, the better the performance is.