Abstract: A parallel wall distance computing approach is proposed for large scale CFD turbulence flow simulations to reduce the wall distance computing time consumption. This method is based on MPI/OpenMP hybrid parallel ADT searching procedure to further improve the computational efficiency and to reduce memory consumption. Firstly, the influence of the accuracy of wall distance computing is analyzed, and the foundational computational geometry algorithm used in this paper is introduced. Then the parallel wall distance computing approach based on the ADT searching procedure is discussed in details. In this method, the total computational field is divided into a number of zones firstly, and then the whole surface faces data on the solid wall is collected and broadcasted to all other processors using MPI communications. The wall distances of spatial cells in each zone are computed based on the ADT searching within each processor. In order to overcome the memory limitation, a MPI/OpenMP hybrid parallel method is proposed, and then only one or a few copies of the surface faces data are created within each computer node other than for each processor. Numerical results show that the present method substantially improves efficiency by one order and reduces the memory consumption by 70%, which indicates that this method can fullfill the demand of large-scale parallel simulations.