US Participation at the Twenty-sixth Internaltional Domain Decomposition Conference

科学计算是一个重要而普遍的交叉学科研究领域，在科学和工程的许多应用领域发挥着至关重要的作用。近年来，由于拥有数百万核的新的高性能计算(HPC)集群，大规模科学计算的需求和计算能力都有了巨大的增长。区域分解方法代表了高效并行求解大规模科学问题的最强大和最通用的技术之一。本项目的目标是为美国的早期职业研究人员，即研究生和博士后，提供资金支持，以参加2019年12月2-6日在香港举行的第26届国际区域分解方法会议。这次会议是被认为是应用数学和计算数学领域最成功的系列之一的一部分。NSF资助的美国参与者将受益于了解区域分解方法的前沿发展和高性能计算的最新全球趋势。他们还将有机会与来自亚洲和世界各地的其他研究人员开展新的合作。该提案将支持最多10名参与者前往这个研讨会，其中一些人预计将是美国大学的研究生。区域分解方法(DDM)可以被视为一种分而治之的策略，用于解决物理领域中提出的数学问题，将一个大问题简化为许多较小但更容易解决的问题。它们特别适合于有效利用分布式内存体系结构，该体系结构能够并行解决许多此类较小的问题。当我们接近亿级计算的曙光时，这种可扩展的技术是解决物理和工程中的复杂问题的重要工具，否则这些问题将是难以解决的。自1987年以来，区域分解方法国际会议已在亚洲、欧洲和北美的15个国家举行。在这个现已是第26届的会议上，域分解及相关领域的研究人员将介绍和讨论最新的方法和发展，并提出高性能计算的未来方向。早期职业研究人员将能够通过三种方式之一参与：作为由其他参与者组织的小型研讨会的演讲者，通过发表贡献的演讲，或者通过展示海报。NSF资助的美国参与者由研究生、博士后和其他缺乏资金的早期职业研究人员组成，他们将受益于学习域分解方法的新发展和高性能计算的最新趋势。会议网站上有更多详细信息：https://www.math.cuhk.edu.hk/conference/dd26/?Conference-HomeThis奖反映了美国国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.