流多处理器上多种全玻尔兹曼的不连续Galerkin快速谱方法

S. Jaiswal, Jingwei Hu, J. Brillon, Alina A. Alexeenko
{"title":"流多处理器上多种全玻尔兹曼的不连续Galerkin快速谱方法","authors":"S. Jaiswal, Jingwei Hu, J. Brillon, Alina A. Alexeenko","doi":"10.1145/3324989.3325714","DOIUrl":null,"url":null,"abstract":"When the molecules of a gaseous system are far apart, say in microscale gas flows where the surface to volume ratio is high and hence the surface forces dominant, the molecule-surface interactions lead to the formation of a local thermodynamically non-equilibrium region extending few mean free paths from the surface. The dynamics of such systems is accurately described by Boltzmann equation. However, the multi-dimensional nature of Boltzmann equation presents a huge computational challenge. With the recent mathematical developments and the advent of petascale, the dynamics of full Boltzmann equation is now tractable. We present an implementation of the recently introduced multi-species discontinuous Galerkin fast spectral (DGFS) method for solving full Boltzmann on streaming multi-processors. The present implementation solves the inhomogeneous Boltzmann equation in span of few minutes, making it at least two order-of-magnitude faster than the present state-of-art stochastic method---direct simulation Monte Carlo---widely used for solving Boltzmann equation. Various performance metrics, such as weak/strong scaling have been presented. A parallel efficiency of 0.96--0.99 is demonstrated on 36 Nvidia Tesla-P100 GPUs.","PeriodicalId":174137,"journal":{"name":"Proceedings of the Platform for Advanced Scientific Computing Conference","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Discontinuous Galerkin Fast Spectral Method for Multi-Species Full Boltzmann on Streaming Multi-Processors\",\"authors\":\"S. Jaiswal, Jingwei Hu, J. Brillon, Alina A. Alexeenko\",\"doi\":\"10.1145/3324989.3325714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When the molecules of a gaseous system are far apart, say in microscale gas flows where the surface to volume ratio is high and hence the surface forces dominant, the molecule-surface interactions lead to the formation of a local thermodynamically non-equilibrium region extending few mean free paths from the surface. The dynamics of such systems is accurately described by Boltzmann equation. However, the multi-dimensional nature of Boltzmann equation presents a huge computational challenge. With the recent mathematical developments and the advent of petascale, the dynamics of full Boltzmann equation is now tractable. We present an implementation of the recently introduced multi-species discontinuous Galerkin fast spectral (DGFS) method for solving full Boltzmann on streaming multi-processors. The present implementation solves the inhomogeneous Boltzmann equation in span of few minutes, making it at least two order-of-magnitude faster than the present state-of-art stochastic method---direct simulation Monte Carlo---widely used for solving Boltzmann equation. Various performance metrics, such as weak/strong scaling have been presented. A parallel efficiency of 0.96--0.99 is demonstrated on 36 Nvidia Tesla-P100 GPUs.\",\"PeriodicalId\":174137,\"journal\":{\"name\":\"Proceedings of the Platform for Advanced Scientific Computing Conference\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Platform for Advanced Scientific Computing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3324989.3325714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Platform for Advanced Scientific Computing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3324989.3325714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

当气体系统的分子距离很远时,比如在表面体积比很高的微尺度气体流动中,因此表面力占主导地位,分子-表面相互作用导致局部热力学非平衡区域的形成,从表面延伸出几个平均自由路径。用玻尔兹曼方程准确地描述了这类系统的动力学。然而,玻尔兹曼方程的多维性给计算带来了巨大的挑战。随着近年来数学的发展和千万亿次的出现,全玻尔兹曼方程的动力学现在是可以处理的。本文提出了一种在流多处理器上求解全玻尔兹曼问题的多物种不连续伽辽金快速谱(DGFS)方法。目前的实现在几分钟内解决了非齐次玻尔兹曼方程,使其比目前最先进的随机方法-直接模拟蒙特卡罗-广泛用于解决玻尔兹曼方程的速度至少快两个数量级。提出了各种性能指标,例如弱/强缩放。在36颗Nvidia Tesla-P100 gpu上实现了0.96—0.99的并行效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Discontinuous Galerkin Fast Spectral Method for Multi-Species Full Boltzmann on Streaming Multi-Processors
When the molecules of a gaseous system are far apart, say in microscale gas flows where the surface to volume ratio is high and hence the surface forces dominant, the molecule-surface interactions lead to the formation of a local thermodynamically non-equilibrium region extending few mean free paths from the surface. The dynamics of such systems is accurately described by Boltzmann equation. However, the multi-dimensional nature of Boltzmann equation presents a huge computational challenge. With the recent mathematical developments and the advent of petascale, the dynamics of full Boltzmann equation is now tractable. We present an implementation of the recently introduced multi-species discontinuous Galerkin fast spectral (DGFS) method for solving full Boltzmann on streaming multi-processors. The present implementation solves the inhomogeneous Boltzmann equation in span of few minutes, making it at least two order-of-magnitude faster than the present state-of-art stochastic method---direct simulation Monte Carlo---widely used for solving Boltzmann equation. Various performance metrics, such as weak/strong scaling have been presented. A parallel efficiency of 0.96--0.99 is demonstrated on 36 Nvidia Tesla-P100 GPUs.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信