Massively parallel grid generation on HPC systems
Massively parallel grid generation on HPC systems
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DOI：
10.1016/j.cma.2014.04.009
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发表时间：
2014-08
影响因子：
7.2
通讯作者：
A. Lintermann;S. Schlimpert;Jerry H. Grimmen;C. Günther;M. Meinke;W. Schröder
中科院分区：
文献类型：
--
作者：
A. Lintermann;S. Schlimpert;Jerry H. Grimmen;C. Günther;M. Meinke;W. Schröder
在高性能计算机上实现网格的自动生成是一项具有挑战性的任务，但其计算能力和内存可用性受到限制。随着对高网格分辨率的需求日益增长，模拟复杂的流动配置需要在具有分布式存储器的多核机器上并行生成网格。在这项研究中，提出了一种新的鲁棒算法，自动生成分层笛卡尔网格的分布式多核HPC系统与多个层次的细化。单元的数量仅受可用内核和内存数量的限制。该算法有效地实现了基于Hilbert曲线的任意核数的计算域分解。通过高容量并行I/O方法高效地存储和访问网格。考虑人体鼻腔和内燃机流动问题的方法的效率被证明。
The automatic grid generation on high performance computers is a challenging task under the restriction of computational power and memory availability. The increasing demand for high grid resolutions to simulate complex flow configurations necessitates parallel grid generation on multicore machines with distributed memory. In this study, a new robust algorithm to automatically generate hierarchical Cartesian meshes on distributed multicore HPC systems with multiple levels of refinement is presented. The number of cells is only restricted by the number of available cores and memory. The algorithm efficiently realizes a computational domain decompositioning for an arbitrary number of cores based on a Hilbert curve. The grids are efficiently stored and accessed via a high capacity parallel I/O method. The efficiency of the approach is demonstrated by considering human nasal cavity and internal combustion engine flow problems.