高性能无网格法粒子系统的设计与实现

G. Bilotta, V. Zago, A. Hérault
{"title":"高性能无网格法粒子系统的设计与实现","authors":"G. Bilotta, V. Zago, A. Hérault","doi":"10.5772/INTECHOPEN.81755","DOIUrl":null,"url":null,"abstract":"Particle systems, commonly associated with computer graphics, animation, and video games, are an essential component in the implementation of numerical methods ranging from the meshfree methods for computational fluid dynamics and related applications (e.g., smoothed particle hydrodynamics, SPH) to minimization methods for arbitrary problems (e.g., particle swarm optimization, PSO). These methods are frequently embarrassingly parallel in nature, making them a natural fit for implementation on massively parallel computational hardware such as modern graphics processing units (GPUs). However, naive implementations fail to fully exploit the capabilities of this hardware. We present practical solutions to the challenges faced in the efficient parallel implementation of these particle systems, with a focus on performance, robustness, and flexibility. The techniques are illustrated through GPUSPH, the first implementation of SPH to run completely on GPU, and currently supporting multi-GPU clusters, uniform precision independent of domain size, and multiple SPH formulations.","PeriodicalId":20515,"journal":{"name":"Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Design and Implementation of Particle Systems for Meshfree Methods with High Performance\",\"authors\":\"G. Bilotta, V. Zago, A. Hérault\",\"doi\":\"10.5772/INTECHOPEN.81755\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Particle systems, commonly associated with computer graphics, animation, and video games, are an essential component in the implementation of numerical methods ranging from the meshfree methods for computational fluid dynamics and related applications (e.g., smoothed particle hydrodynamics, SPH) to minimization methods for arbitrary problems (e.g., particle swarm optimization, PSO). These methods are frequently embarrassingly parallel in nature, making them a natural fit for implementation on massively parallel computational hardware such as modern graphics processing units (GPUs). However, naive implementations fail to fully exploit the capabilities of this hardware. We present practical solutions to the challenges faced in the efficient parallel implementation of these particle systems, with a focus on performance, robustness, and flexibility. The techniques are illustrated through GPUSPH, the first implementation of SPH to run completely on GPU, and currently supporting multi-GPU clusters, uniform precision independent of domain size, and multiple SPH formulations.\",\"PeriodicalId\":20515,\"journal\":{\"name\":\"Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing\",\"volume\":\"46 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5772/INTECHOPEN.81755\",\"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 25th ACM International Symposium on High-Performance Parallel and Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.81755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

粒子系统通常与计算机图形学、动画和视频游戏相关,是实现数值方法的重要组成部分,范围从计算流体动力学的无网格方法及其相关应用(例如,光滑粒子流体动力学,SPH)到任意问题的最小化方法(例如,粒子群优化,PSO)。这些方法在本质上往往是令人尴尬的并行,这使得它们非常适合在大规模并行计算硬件(如现代图形处理单元(gpu))上实现。然而,幼稚的实现不能充分利用这种硬件的功能。我们针对这些粒子系统的高效并行实现所面临的挑战提出了切实可行的解决方案,重点关注性能、鲁棒性和灵活性。GPUSPH是第一个完全在GPU上运行的SPH实现,目前支持多GPU集群、独立于域大小的均匀精度和多种SPH公式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of Particle Systems for Meshfree Methods with High Performance
Particle systems, commonly associated with computer graphics, animation, and video games, are an essential component in the implementation of numerical methods ranging from the meshfree methods for computational fluid dynamics and related applications (e.g., smoothed particle hydrodynamics, SPH) to minimization methods for arbitrary problems (e.g., particle swarm optimization, PSO). These methods are frequently embarrassingly parallel in nature, making them a natural fit for implementation on massively parallel computational hardware such as modern graphics processing units (GPUs). However, naive implementations fail to fully exploit the capabilities of this hardware. We present practical solutions to the challenges faced in the efficient parallel implementation of these particle systems, with a focus on performance, robustness, and flexibility. The techniques are illustrated through GPUSPH, the first implementation of SPH to run completely on GPU, and currently supporting multi-GPU clusters, uniform precision independent of domain size, and multiple SPH formulations.
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:481959085
Book学术官方微信