Abstract: Lattice Boltzmann method (LBM) is a novel and promising computational fluid dynamics method, which has natural advantages. From the perspective of algorithm, the iterative process can be divided into parallel programs with multiple subproblems. In order to obtain extremely fast data processing speed, the iterative process is computed by high-performance graphics processing unit(GPU). At the same time, the efficient implementation of GPU-based LBM method has been widely reported, so it is very suitable for high performance image processor (GPU) calculation to obtain extremely fast data processing speed. The program environment is C++ as the programming language, the CUDA program structure is optimized by object-oriented thinking, the coupling of the program is reduced, and the sustainable development of the program is endowed. Poiseuille flow model is used to verify the stability and accuracy of the optimization program. During the program running, CUDA kernel functions are called to deal with the collision within the model, migration flow and iterative process of calculating macro quantities. Meanwhile, shared memory is used to store GPU runtime data to improve computing efficiency. Analysis of the data show that computing speeds are up to 70 times faster than those of the central processing unit (CPU), thanks to the GPU's high-performance parallel computing capabilities.