数据与计算发展前沿2024，Vol.6Issue(5)：148-158,11.DOI:10.11871/jfdc.issn.2096-742X.2024.05.014
物质点法模拟的大规模并行算法
Large Scale Parallel Algorithm for Material Point Method Simulation
摘要
Abstract
[Objective]As a meshless method,the material point method(MPM)is commonly used to solve collision,penetration,and large deformation problems.On the one hand,in order to ac-complish more realistic simulation effects,actual application scenarios involve hundreds of mil-lions of material points and grids.On the other hand,frequent interpolation occurs between the material points and grid nodes.Therefore,a comprehensive consideration of both is necessary to achieve task division.Moreover,since material points are inhomogeneous with relation to the background grid,a flexible division method needs to be designed to achieve workload bal-ancing.Based on it,we design and implement the parallel algorithm to achieve large-scale sim-ulation.[Methods]An adaptive partitioning design is used for MPM to achieve a relatively balanced workload between processes.Then,the communication design is carried out for data dependencies on grid points and mate-rial points moving between processes.Finally,the parallel coupling of material points and grid points is imple-mented.[Results]For solving the penetration problem,its parallel efficiency is more than 80%in the strong scal-ability testing.[Limitations]Due to the continuous movement of material points in space,dynamic load balanc-ing of material points may get better acceleration effects.[Conclusions]We design a parallel algorithm of 3D adaptive partitioning for MPM,which achieves good acceleration effects.The data dependency analysis provides a reference for the design and optimization of dynamic load-balancing strategies in the future.关键词
物质点法/负载均衡/三维并行/大规模Key words
material point method/load balancing/3D parallel/large scale引用本文复制引用
田少博,李佳霖,张鉴..物质点法模拟的大规模并行算法[J].数据与计算发展前沿,2024,6(5):148-158,11.基金项目
国家重点研发计划(2021YFB0300203) （2021YFB0300203）
