Parallelization of the Symplectic Massive Body Algorithm (SyMBA) $N$-body Code

Tommy Chi Ho Lau,Man Hoi Lee

Research notes of the AAS(2023)

引用 0|浏览2
暂无评分
摘要
Direct $N$-body simulations of a large number of particles, especially in the study of planetesimal dynamics and planet formation, have been computationally challenging even with modern machines. This work presents the combination of fully parallelized $N^2/2$ interactions and the incorporation of the GENGA code's close encounter pair grouping strategy to enable MIMD parallelization of the Symplectic Massive Body Algorithm (SyMBA) with OpenMP on multi-core CPUs in shared-memory environment. SyMBAp (SyMBA parallelized) preserves the symplectic nature of SyMBA and shows good scalability, with a speedup of 30.8 times with 56 cores in a simulation with 5,000 fully interactive particles.
更多
查看译文
关键词
symplectic massive body algorithm,symba,n-body
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要