Spatial operations such as spatial join combine two objects on spatial predicates. It is different from relational join because objects have multi dimensions and spatial join consumes large execution time. Recently, many works investigate methods to improve the execution time. Parallel spatial join is one of the methods. Comparison between objects can be done in parallel. Because spatial datasets are large, R-Tree data structure is used improve the performance of the access to data. In this paper, we design a parallel spatial join on Graphics processing unit (GPU). We use GPU which has many processors to accelerate the computation. The experiment is carried out to compare the spatial join between a sequential implementation with C language on CPU and a parallel implementation with CUDA C language on GPU. The result shows that the spatial join on GPU is faster than on a conventional processor.
