Using overset grid can effectively handle problems with large-scale motions.However,as the scale of the grid and the complexity of the flow problem increase,traditional CPU-based overset grid assembly methods are becoming increasingly difficult to meet current computational demands.To address these issues,this paper develops a GPU-based k-d tree nested grid assembly method based on the CUDA platform,and optimizes the k-d tree construction process and search process,which greatly improves the contribution unit search efficiency and object-surface distance calculation efficiency,thereby accelerating the nested grid assembly speed.
关键词
图形处理器/嵌套网格/k-d树/装配方法/流场计算域
Key words
graphics processor/nested grid/k-d tree/assembly method/flow field computing domain
维普
万方数据