Twentieth International Conference on Domain Decomposition Methods

该NSF奖将为第20届领域分解方法国际会议提供部分资金支持，该会议将于2011年2月在加州大学圣地亚哥分校的圣地亚哥超级计算机中心举行。在某种形式下，域分解是迄今为止在大规模并行分布式分层存储计算机上进行大规模模拟的最常见范例。这种范式几乎渗透到模拟的所有领域，从数值气候建模、复杂生物分子和生物过程的建模、汽车、飞机和其他结构的设计和测试、复杂多孔介质流的建模等实际问题，到更抽象的科学努力，如黑洞建模和寻找宇宙起源。然而，许多领域分解的用户并没有利用已知的最复杂和最有效的方法。在过去几年中，随着大规模科学模拟社区的规模随着硬件的可用性而增长，特别是在与计算数学或计算机科学社区没有传统紧密联系的科学社区中，这一点变得更加明显。本次会议的目标是通过鼓励国际计算科学和工程社区的跨学科技术交流，并利用会议地点的优势，促进领域分解方法的进步，吸引许多新的美国科学家进入这一重要领域。它与美国国家科学基金会，更广泛地说，与我们国家的优先事项密切相关，以促进和推进计算科学与工程领域的基础跨学科研究。NSF的资金将为研究生、博士后和其他可能无法参加的年轻研究人员提供可能的经济支持。这笔资金还将允许来自全国各地的妇女、非洲裔美国人和西班牙裔美国人以及来自南加州不同科学界的更多参与。

This NSF award will provide partial financial support for the Twentieth International Conference on Domain Decomposition Methods, to be held at the San Diego Supercomputer Center on the campus of the University of California at San Diego, in February 2011. Domain decomposition, in some form, is by far the most common paradigm for large-scale simulation on massively parallel distributed, hierarchical memory computers. This paradigm permeates almost all arenas of simulation, from such practical concerns as numerical climate modeling, modeling of complex biological molecules and biological processes, the design and testing of automobiles, aircraft and other structures, and the modeling of complex porous media flows, to more abstract scientific endeavors such as modeling black holes and searching for the origins of the universe. However, many users of domain decomposition do not avail themselves of the most sophisticated and efficient methods known. This has become more pronounced as the size of the large-scale scientific simulation community has grown with the availability of hardware in the past few years, particularly inside scientific communities without traditionally strong ties to the computational mathematics or computer science communities.The goal of this conference is to promote advances in domain decomposition methods by encouraging interdisciplinary technical interchange throughout the international computational science and engineering communities, and by taking advantage of conference siting, to attract to this important area many new U.S. scientists. It is strongly aligned with NSF's, and more generally, our national priorities to promote and advance fundamental interdisciplinary research in Computational Science and Engineering.NSF funding will make possible financial support for graduate students, post-docs, and other young researchers who otherwise might not be able to attend. The funding will also allow for increasing participation of women, African Americans, and Hispanic Americans from across the nation as well as from the diverse Southern California scientific community.