3D raster is an ideal model which performs really well at the aspects of detailed representation and spatial interpolation for internal attributes of spatial entities. However, due to the large scale of raster data, rasterizing efficiency and data compression still remain the bottlenecks in practical applications. The present situation of rasterization algorithms for 3D vector model was comprehensively reviewed. In order to improve the time efficiency of 3D vector-raster conversion and save storage space of raster data, a Parallel Ternary Axes Scan (P-TAS) algorithm, which could run on the new multi-core CPU and high performance computer cluster, was designed for transforming 3D vector model to raster model with Octree structure by using MPI parallel techniques. Furthermore, the Boolean operation algorithm for 3D spatial entities represented with multi-granularity raster was designed for the dynamic simulation of underground excavation process. The experiment results demonstrate that the parallel efficiency of P-TAS is about 50%—60% and the data compression ratio is about 80%. The high application values of P-TAS and Boolean algorithms proposed are proved up to the hilt.