U.S.-France (INRIA) Cooperative Research: Domain Decomposition and Multilevel Techniques in Large-Scale Parallel Computing

美法（INRIA）合作研究：大规模并行计算中的领域分解和多级技术

• 批准号: 9310529
• 负责人: Steve McCormick
• 金额: $ 3.63万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-06-01 至 1997-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9310529&HistoricalAwards=false
• 关键词: U.S.; France; INRIA; Cooperative; Research

9310529 McCormick This three-year award supports U.S.-France cooperative research in applied mathematics and advanced scientific computing among U.S. and French research teams at the University of Colorado (Denver and Boulder), Texas A&M, and INRIA Rocquencourt (French National Institute for Research in Computer Science and Applied Mathematics) and ONERA. The objective of the research is to investigate domain decomposition and multilevel techniques for parallel numerical simulation of fluid flow and structural dynamics. The idea behind this approach is to develop new methods in a parallel computing environment to allow modeling of more sophisticated engineering problems. They will focus the research on four applications: (1) flow transition to turbulence; (2) zoning-coupled flow modeling; (3) transport phenomena; and (4) fluid-structure interaction. The proposed areas arise in many civil and aerospace engineering applications. The U.S. investigators bring to this collaboration expertise in parallel computing, multilevel and domain decomposition techniques. This is complemented by the French team's experience in domain decomposition, fluid flow and parallel computing. Their joint efforts could lead to improved algorithms for large scale parallel computing. ***

小行星9310529 这个为期三年的奖项支持美国-法国合作研究应用数学和先进的科学计算之间的美国和法国的研究小组在科罗拉多大学（丹佛和博尔德），得克萨斯州A M，和INRIA罗昆科特（法国国家研究所在计算机科学和应用数学）和ONERA。 本研究的目的是探讨区域分解和多层技术的并行数值模拟的流体流动和结构动力学。 这种方法背后的想法是在并行计算环境中开发新方法，以允许对更复杂的工程问题进行建模。 他们将集中研究四个应用：（1）流动过渡到湍流;（2）分区耦合流动建模;（3）传输现象;（4）流体-结构相互作用。 提出的领域出现在许多民用和航空航天工程应用。 美国调查人员为这次合作带来了并行计算、多级和域分解技术方面的专业知识。 法国团队在区域分解、流体流动和并行计算方面的经验对此进行了补充。 他们的共同努力可能会导致大规模并行计算的改进算法。 ***