西安电子科技大学学报（自然科学版）Issue(1)：194-199,212,7.DOI:10.3969/j.issn.1001-2400.2015.01.031
时域有限差分法中的GP U加速高效CP ML方案
High performance CPML acceleration scheme with GPU for FDTD
摘要
Abstract
To overcome computational redundancy and memory-access redundancy of the traditional GPU-accelerated CPML technique,a novel division-free and minimum-access CPML scheme is proposed.In the proposed scheme,the division operators in the CPML method are merged into a series of fixed coefficients by optimally rearranging the iteration process of CPML and then,the reduplicate memory accesses are eliminated by updating the FDTD and CPML operation in the PML region jointly.Experimental results show that the proposed structure can save up to 70% operation time compared with the traditional GPU-CPML technique and 44% of field updating in the PML region,without any loss of accuracy.关键词
时域有限差分法/卷积完全匹配层/图形处理器/并行计算/计算统一设备架构Key words
finite difference time domain method/convolution perfectly matched layer/graphics processing unit/parallel computing/compute unified device architecture分类
信息技术与安全科学引用本文复制引用
白冰,牛中奇..时域有限差分法中的GP U加速高效CP ML方案[J].西安电子科技大学学报（自然科学版）,2015,(1):194-199,212,7.基金项目
国家自然科学基金资助项目(30870577,61301288) （30870577,61301288）
中央高校基本科研业务费资助项目(JB140218,K5051302057) （JB140218,K5051302057）
