In this work, we describe a multidimensional sequence model and then represent a parallel algorithm. We improve the primary parallel algorithm with two modification rules. Two approaches follow the level-wise approach and all participating processors or workers generate candidate sequences and count their supports independently. Our experiments show good load balancing and scalable and acceptable speedup over different processors and problem sizes and demonstrate that our approach can works efficiently in a real parallel computing environment.