摘要
实现了基于计算统一设备架构(CUDA)的直接模拟Monte Carlo(DSMC)并行算法,改进了原有多图形处理器(GPU)数据之间传输并行算法,数值模拟计算二维Couette流和二维顶盖驱动方腔流,定量比较了CPU、单GPU和多GPU并行计算的结果和计算时间.结果表明单GPU并行计算相对CPU计算的加速效果可以达到10~30倍,双GPU并行计算加速效果可以达到40~60倍,多GPU并行计算的加速效率接近100%,且计算精度能够得到良好保证.
Parallel computing of direct simulation Monte Carlo ( DSMC) based on compute unified device architecture ( CUDA) is developed and improved data transmission in multi-GPU parallel computing is devoted to promote parallel efficiency. A two-dimensional Couette flow and lid-driven cavity flow by CPU, single GPU and double GPU parallel computing are simulated, respectively. Precision of results by GPU is consistent with that by CPU and speedup ratio can reach to 10~30 by single GPU acceleration and 40~60 by double GPU acceleration. Speedup efficiency by multi-GPU is approximated to 100%.
出处
《计算物理》
CSCD
北大核心
2015年第2期169-176,共8页
Chinese Journal of Computational Physics
基金
国家自然科学基金(51276077
51390494)
教育部新世纪优秀人才支持计划(NCET-10-0395)
多相复杂系统国家重点实验室开放课题(MPCS-2011-D-02)资助项目