A Parallel Algorithm Using Perlin Noise Superposition Method for Terrain Generation Based on CUDA architecture

A parallel algorithm for terrain generation based on CUDA architecture is proposed in this paper, which aims to address the problems of high computational load and low efficiency when generating large scale terrains using the Perlin noise superposition method. The Perlin noise superposition method is combined with independent calculation of each point based on the characteristics of all adjacent points. The Perlin noise value of each terrain grid point is transferred to a GPU thread for calculation, so that the terrain generation process is executed in completely parallel in the GPU. Experimental results show that The GPU algorithm generates a grid of size 25000000 (25 million grid points) needs only 0.6355 s, while the original CPU algorithm takes 23.3723 s, so, the parallel processing algorithm can improve the efficiency of the terrain generation and meet the requirements for large-scale terrain generation compared with the original algorithm.