计算机科学
多边形网格
可扩展性
并行计算
计算科学
网格生成
T顶点
巨量平行
橡树岭国家实验室
缩放比例
超级计算机
计算机图形学(图像)
物理
有限元法
数据库
热力学
核物理学
数学
几何学
作者
Gerrett Diamond,Cameron Smith,Chonglin Zhang,Eisung Yoon,Mark S. Shephard
标识
DOI:10.1016/j.jpdc.2021.06.004
摘要
Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. This paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations.
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