p-adaptive discontinuous Galerkin method for the shallow water equations on heterogeneous computing architectures.
CoRR(2023)
摘要
Heterogeneous computing and exploiting integrated CPU-GPU architectures has
become a clear current trend since the flattening of Moore's Law. In this work,
we propose a numerical and algorithmic re-design of a p-adaptive
quadrature-free discontinuous Galerkin method (DG) for the shallow water
equations (SWE). Our new approach separates the computations of the
non-adaptive (lower-order) and adaptive (higher-order) parts of the
discretization form each other. Thereby, we can overlap computations of the
lower-order and the higher-order DG solution components. Furthermore, we
investigate execution times of main computational kernels and use automatic
code generation to optimize their distribution between the CPU and GPU. Several
setups, including a prototype of a tsunami simulation in a tide-driven flow
scenario, are investigated, and the results show that significant performance
improvements can be achieved in suitable setups.
更多查看译文
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