US Participation at the Twenty-sixth Internaltional Domain Decomposition Conference

美国参加第二十六届国际域分解会议

• 批准号: 1930036
• 负责人: Jinchao Xu
• 金额: $ 1.5万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2021-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1930036&HistoricalAwards=false
• 关键词: US; Participation; Twenty; sixth; Internaltional

Scientific computing is an important and general interdisciplinary research field and plays a crucial role in many application areas in science and engineering. In recent years, there has been tremendous growth in both the need for large-scale scientific computing and the amount of computing power, thanks to new high performance computing (HPC) clusters with millions of cores. Domain decomposition methods represent one of the most powerful and versatile techniques for the efficient parallel solution of such large-scale scientific problems. The goal of the current project is to provide financial support for US-based early career researchers, i.e., graduate students and post-docs, to attend the 26th International Conference on Domain Decomposition Methods, to be held in Hong Kong from December 2-6, 2019. The conference is part of a series that is considered one of the most successful in Applied and Computational Mathematics. The NSF-funded US participants will benefit from learning about cutting-edge developments in domain decomposition methods and latest worldwide trends in high performance computing. They will also have the opportunity to develop new collaborations with other researchers from Asia and around the world. The proposal will support up to 10 participants to travel to this workshop and some of these 10 are expected to be graduate students at US universities.Domain decomposition methods (DDM) can be regarded as a divide-and-conquer strategy for solving mathematical problems posed in a physical domain, reducing a large problem into many smaller, but easier-to-solve, problems. They are particularly suited for making efficient use of distributed memory architectures, which are able to solve many such smaller problems in parallel. As we approach the dawn of exascale computing, such scalable techniques are vital tools for solving complex problems in physics and engineering that would otherwise be intractable. Since 1987, the International Conferences of Domain Decomposition Methods have been held in 15 countries throughout Asia, Europe and North America. In this conference, now in its 26th edition, researchers in domain decomposition and related fields will present and discuss state-of-the-art methodologies and developments and propose future directions in high performance computing. Early career researchers will be able to participate in one of three ways: as speakers at a minisymposium organized by fellow participants, by giving a contributed talk, or by presenting a poster. The NSF-funded US participants, consisting of graduate students, postdocs and other early career researchers who lack their own funding, will benefit from learning new developments in domain decomposition methods and latest trends in high performance computing. MOre details are available at the conference website: https://www.math.cuhk.edu.hk/conference/dd26/?Conference-HomeThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

科学计算是一个重要且一般的跨学科研究领域，在科学和工程的许多应用领域中起着至关重要的作用。近年来，由于新的高性能计算（HPC）集群，对大规模科学计算的需求和计算能力的数量都有巨大的增长。域分解方法代表了这种大规模科学问题的有效平行解决方案最强大，最通用的技术之一。当前项目的目的是为美国早期职业研究人员（即研究生和毕业后）提供财政支持，以参加2019年12月2日至6日在香港举行的第26届国际领域分解方法会议。该会议是一系列的一部分，被认为是在应用和计算数学领域最成功的系列。 NSF资助的美国参与者将受益于了解域分解方法中的尖端发展以及高性能计算中最新的全球趋势。他们还将有机会与亚洲和世界各地的其他研究人员建立新的合作。该提案将支持多达10名参与者前往该研讨会，预计这10个将是美国大学的研究生。域分解方法（DDM）可以被视为一种解决在物理领域中构成的数学问题的分裂和争议策略，将一个较小的问题减少到许多较小的问题，但更容易，但更容易解决问题。它们特别适合有效利用分布式内存体系结构，这些内存体系结构能够并行解决许多如此较小的问题。当我们接近Exascale计算的曙光时，这种可扩展的技术是解决物理和工程中复杂问题的重要工具，否则这将是棘手的。自1987年以来，在亚洲，欧洲和北美的15个国家举行了国际域分解方法的会议。在本次会议上，在第26版中，领域分解和相关领域的研究人员将介绍和讨论最先进的方法论和发展，并提出高性能计算中未来的方向。早期的职业研究人员将能够以三种方式参与：作为同伴们组织的小型人物的演讲者，通过发表贡献或介绍海报来组织。 NSF资助的美国参与者，由研究生，博士后和其他缺乏自己资金的早期职业研究人员组成，将受益于学习领域分解方法的新发展以及高性能计算的最新趋势。会议网站上提供更多详细信息：https：//www.math.cuhk.edu.hk/conference/dd26/?conference-homethis Award反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来通过评估来获得支持的。