计算机科学 ›› 2024, Vol. 51 ›› Issue (9): 31-39.doi: 10.11896/jsjkx.230300188
林拥真1,2, 徐传福1,2, 邱昊中1,2, 汪青松1,2, 王正华2, 杨富翔3,4, 李洁3
LIN Yongzhen1,2, XU Chuanfu1,2, QIU Haozhong1,2, WANG Qingsong1,2, WANG Zhenghua2, YANG Fuxiang3,4, LI Jie3
摘要： DSMC/PIC耦合模拟是一类重要的高性能计算应用,大规模DSMC/PIC耦合模拟计算量巨大,需要实现高效并行计算。由于粒子动态注入、迁移等操作,基于MPI并行的DSMC/PIC耦合模拟往往通信开销较大且难以实现负载均衡。针对自主研发的DSMC/PIC耦合模拟软件,在原有MPI并行优化版本上设计实现了高效的MPI+CUDA异构并行算法,结合GPU体系结构和DSMC/PIC计算特点,开展了GPU访存优化、GPU线程工作负载优化、CPU-GPU数据传输优化及DSMC/PIC数据冲突优化等一系列性能优化。在北京北龙超级云HPC系统的NVIDIA V100和A100 GPU上,针对数亿粒子规模的脉冲真空弧等离子体羽流应用,开展了大规模DSMC/PIC耦合异构并行模拟,相比原有纯MPI并行,GPU异构并行大幅缩短了模拟时间,两块GPU卡较192核的CPU加速比达到550%,同时具有更好的强可扩展性。
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