CAJ | 학술논문

非结构网格的生成在时间和内存上有一定的缺陷，这里提出了一种新的方法，命名为GPU-PDMG，是基于CUDA架构的GPU并行非结构网格生成技术。该技术结合了GPU的高速并行计算能力与Delaunay三角化的优点，在英伟达GPU模块下采用CUDA程序模型，开发出了加锁并行区划分技术，通过对NACA0012翼型、多段翼型等算例进行测试，分析此方法的加速比和效率，对其计算性能展开评估。实验结果表明，GPU-PDMG优于现存在的CPU算法的速度，在保证网格质量的同时，提高了效率。
비결구망격적생성재시간화내존상유일정적결함，저리제출료일충신적방법，명명위GPU-PDMG，시기우CUDA가구적GPU병행비결구망격생성기술。해기술결합료GPU적고속병행계산능력여Delaunay삼각화적우점，재영위체GPU모괴하채용CUDA정서모형，개발출료가쇄병행구화분기술，통과대NACA0012익형、다단익형등산례진행측시，분석차방법적가속비화효솔，대기계산성능전개평고。실험결과표명，GPU-PDMG우우현존재적CPU산법적속도，재보증망격질량적동시，제고료효솔。
Defects of consuming time and memory consist in unstructured mesh generation. This paper proposes a novel approach, terming GPU-PDMG, which is GPU parallel unstructured mesh generation based on the framework of CUDA. The technology combines the high-speed parallel GPU and advantages of Delaunay triangulation. It develops a method of locking parallel area dividing, using the CUDA programming model on nVidia GPUs. By analyzing the tested examples’ speedup rate and efficiency, it has evaluated their computing performance. This result is identified in NACA0012 and multi-element airfoil experiment with both the analysis of speedup rate and efficiency and GPU-PDMG is better than any existing GPU algorithms.