Aiming at the problem of optimal siting of charging station for electric taxis, a siting model of charging station for electric taxis was established with the unmet charging demand and the minimum fixed cost of constructing new charging station as objective functions, and a model solution method based on improved multi-objective particle swarm optimization was proposed. In order to solve the performance bottleneck of computing unmet charging demand, a Graphics Processing Unit (GPU)-based unmet charging demand parallel algorithm was designed. Experimental results demonstrat that the running time of the parallel algorithm is about 10%-12% of that of CPU-based serial algorithm. Beijing was taken as an example of applying the proposed charging station siting model, and related multi-source data was collected and processed. The results show that the proposed optimal siting scheme for charging station is feasible.