Suppr超能文献

用于OpenFOAM中辐射传输模拟的离散坐标法的优化与并行化:共享内存和分布式内存方法的分层组合

Optimization and parallelization of the discrete ordinate method for radiation transport simulation in OpenFOAM: Hierarchical combination of shared and distributed memory approaches.

作者信息

Moreno-SanSegundo Jose, Casado Cintia, Concha David, Montemayor Antonio S, Marugán Javier

机构信息

Department of Chemical and Environmental Technology, Universidad Rey Juan Carlos, Móstoles, Madrid, 28933, Spain.

Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Móstoles, Madrid, 28933, Spain.

出版信息

Open Res Eur. 2021 Mar 24;1:2. doi: 10.12688/openreseurope.13017.1. eCollection 2021.

Abstract

This paper describes the reduction in memory and computational time for the simulation of complex radiation transport problems with the discrete ordinate method (DOM) model in the open-source computational fluid dynamics platform OpenFOAM. Finite volume models require storage of vector variables in each spatial cell; DOM introduces two additional discretizations, in direction and wavelength, making memory a limiting factor. Using specific classes for radiation sources data, changing the store of fluxes and other minor changes allowed a reduction of 75% in memory requirements. Besides, a hierarchical parallelization was developed, where each node of the standard parallelization uses several computing threads, allowing higher speed and scalability of the problem. This architecture, combined with optimization of some parts of the code, allowed a global speedup of x15. This relevant reduction in time and memory of radiation transport opens a new horizon of applications previously unaffordable.

摘要

本文描述了在开源计算流体动力学平台OpenFOAM中,使用离散坐标法(DOM)模型模拟复杂辐射传输问题时内存和计算时间的减少。有限体积模型需要在每个空间单元中存储向量变量;DOM在方向和波长上引入了另外两种离散化方法,使得内存成为一个限制因素。通过使用特定的辐射源数据类、改变通量存储方式以及其他一些小的改变,内存需求减少了75%。此外,还开发了一种分层并行化方法,标准并行化的每个节点使用多个计算线程,从而提高了问题的求解速度和可扩展性。这种架构与代码部分优化相结合,实现了15倍的全局加速。辐射传输在时间和内存上的这种显著减少为以前无法实现的新应用开辟了前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84fd/10445830/87d68ffc1d92/openreseurope-1-14087-g0000.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验