Earthquake Ground Motion Modeling in Large Basins

大盆地地震地面运动模拟

• 批准号: 9318163
• 负责人: Jacobo Bielak
• 金额: $ 215.4万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-09-01 至 2000-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9318163&HistoricalAwards=false
• 关键词: Earthquake; Ground; Motion; Modeling; Large

9318163 Bielak The Grand Challenge Application Groups competition provides one mechanism for the support of multidisciplinary teams of scientists and engineers to meet the goals of the High Performance Computing and Communications (HPCC) Initiative in Fiscal Year 1993. The ideal proposal provided not only the opportunity to achieve significant progress on (1) a fundamental problem in science or engineering whose solution could be advanced by applying high performance computing techniques and resources, or (2) enabling technologies which facilitate those advances. but also significant interactions between scientific and computational activities, usually involving mathematical, computer or computational scientist, that would have impact in high performance computational activities beyond the specific scientific or engineering problem area(s) or discipline being studied. The main objective of the proposed research is to develop and demonstrate the capability for predicting, by computer simulation the ground motion of large basins during strong earthquakes, and to use this capability to study the seismic response of the Greater Los Angeles Basin. The proposed research seeks to: 1. Develop three-dimensional models of large-scale, heterogeneous basins that take into account earthquake source, propagation path, and site conditions; 2. Develop nonlinear models for sedimentary basins that experience sufficiently strong ground motion; 3. Develop unstructured mesh methods and associated fast parallel solvers, enabling the study of much larger basins; 4. Develop software tools for the automatic mapping of the computations associated with large unstructured mesh problems on parallel computers; 5. Characterize the computation and communication requirements of unstructured mesh problems, and make a set of recommendations for the design of future parallel systems. While the proposed work is motivated by an interest in gaining a better understanding of strong se ismic motion in large basins, the algorithms and software tools developed will be applicable to a wide range of applications that require unstructured meshes. This award is being supported by the Advanced Projects Research Agency as well as NSF programs in engineering, atmospheric and computer sciences. 9318183 Davis The Grand Challenge Application Groups competition provides one mechanism for the support of multidisciplinary teams of scientists and engineers to meet the goals of the High Performance Computing and Communications (HPCC) Initiative in Fiscal Year 1993. The ideal proposal provided not only the opportunity to achieve significant progress on (1) a fundamental problem in science or engineering whose solution could be advanced by applying high performance computing techniques and resources, or (2) enabling technologies which facilitate those advances but also significant interactions between scientific and computational activities, usually involving mathematical, computer or computational scientist, that would have impact in high performance computational activities beyond the specific scientific or engineering problem area(s) or discipline being studied. The investigators will study the application of high performance parallel computing to a class of scientifically important and computationally demanding problems in remote sensing-land cover dynamics problems including generating improved fine spatial resolution data for the global carbon cycle, hydrological modeling and global ecological responses to climate changes and human activity. The research is collaborative, including scientist from the University of Maryland, University of Indiana, University of news Hampshire and NASA s Goddard Space Center. The award will combine research on -new analysis procedures for remotely sensed data -the integration of multispectral, multiresolution and multitemporal image data sets into a unified global data structure based on hie rarchical data structures (i.e., quadtrees) -the utilization of these hierarchical, parallel data structures for the representation of spatial data (maps and products developed from image analysis) and the development of a spatial data base system with a sophisticated query language that scientist can use to control the application of biophysical models to global data sets -run-time support for constructing scalable and parallel solutions to problems involving the manipulation of irregular data structures such as quadtrees -parallel I/O,especially novel methods for mapping large arrays and quadtrees onto parallel disks and disk systems, and for accessing them using low overhead bulk transfers The development work will be conducted on a 32 processor Connection Machine CM5, installed at the University of Maryland, and on an IBM SP1 which we propose to obtain as part of the program. This award is being supported by the Advanced Projects Research Agency as well as NSF programs in geological, biological, and computer sciences. 9318145 Messina The Grand Challenge Application Groups competition provides one mechanism for the support of multidisciplinary teams of scientists and engineers to meet the goals of the High Performance Computing and Communications (HPCC) Initiative in Fiscal Year 1993. The ideal proposal provided not only the opportunity to achieve significant progress on (1) a fundamental problem in science or engineering whose solution could be advanced by applying high performance computing techniques and resources, or (2) enabling technologies which facilitate those advances. but also significant interactions between scientific and computational activities, usually involving mathematical, computer or computational scientist, that would have impact in high performance computational activities beyond the specific scientific or engineering problem area(s) or discipline being studied. This multi-disciplinary project will investigate and develop strategies for efficient implementation of I/O intensive applications in computational science and engineering. Scalable parallel I/O approaches will be pursued by a team of computer scientists and applications scientists who will work together to: * Characterize the I/O behavior of specific application programs running on large massively parallelcomputers * Abstract and define I/O models (templates) * Define application-level methodologies for efficient parallel I/O * Implement and test application level I/O tools on large-scale computers The Pablo performance analysis environment will provide the foundation for the performance instrumentation and analysis. The application programs are already fully operational on advanced architecture systems and their authors are all co-investigators in this project. The principal computers used will be the Intel Touchstone Delta and Paragon systems at Caltech, each with over 500 computational nodes. Five application areas will be included: fluid dynamics, chemistry, astronomy, neuroscience, and modelling of materials-processing plasmas. The parallel programs for these applications cover a range of I/O patterns and volume, and the techniques that will be developed in this project will be of relevance to a broad spectrum of engineering and science applications. In addition, by overcoming their current I/O limitations, the specific applications targeted in this award will achieve significant new science and engineering results. By the end of the project, sustained teraFLOPS computers will become available. The project will devise and implement general methods for scalable I/O using today's advanced computers, immediately apply those methods to carry out unprecedented applications in several fields, and use the

Bielak大挑战应用小组竞赛为支持多学科科学家和工程师团队提供了一种机制，以实现1993财政年度高性能计算和通信（HPCC）计划的目标。理想的提案不仅提供了在(1)科学或工程的基本问题上取得重大进展的机会，其解决方案可以通过应用高性能计算技术和资源来推进，或者(2)促进这些进步的启用技术。而且科学和计算活动之间也有重要的相互作用，通常涉及数学、计算机或计算科学家，这将对高性能计算活动产生影响，超出特定的科学或工程问题领域或正在研究的学科。提出的研究的主要目的是发展和展示通过计算机模拟强震期间大型盆地地面运动的预测能力，并利用这种能力研究大洛杉矶盆地的地震反应。拟议的研究旨在：1。建立考虑震源、传播路径和场地条件的大尺度非均质盆地的三维模型；2. 为经历强烈地面运动的沉积盆地建立非线性模型；3. 开发非结构化网格方法和相关的快速并行求解器，使研究更大的盆地成为可能；4. 开发软件工具，用于在并行计算机上自动映射与大型非结构化网格问题相关的计算；5. 描述了非结构化网格问题的计算和通信需求，并对未来并行系统的设计提出了一套建议。虽然这项工作的动机是为了更好地了解大型盆地的强地震运动，但所开发的算法和软件工具将适用于需要非结构化网格的广泛应用。该奖项由高级项目研究局以及美国国家科学基金会在工程、大气和计算机科学方面的项目提供支持。9318183戴维斯大挑战应用小组竞赛为支持多学科科学家和工程师团队提供了一种机制，以实现1993财政年度高性能计算和通信（HPCC）计划的目标。理想的提案不仅提供了在以下方面取得重大进展的机会：(1)科学或工程中的基本问题，其解决方案可以通过应用高性能计算技术和资源来推进，或(2)促进这些进展的使能技术，而且还提供了科学和计算活动之间的重要互动，通常涉及数学、计算机或计算科学家；这将对正在研究的特定科学或工程问题领域或学科之外的高性能计算活动产生影响。研究人员将研究高性能并行计算在遥感土地覆盖动力学问题中的应用，这些问题具有重要的科学意义和计算要求，包括为全球碳循环、水文建模和气候变化和人类活动的全球生态响应生成改进的精细空间分辨率数据。这项研究是由马里兰大学、印第安纳大学、新罕布什尔大学和美国宇航局戈达德航天中心的科学家合作进行的。该合同将结合对遥感数据新分析程序的研究，将多光谱、多分辨率和多时间图像数据集集成到基于分层数据结构（即四叉树）的统一全球数据结构中。用于表示空间数据（从图像分析开发的地图和产品）的并行数据结构和具有复杂查询语言的空间数据库系统的开发，科学家可以使用该查询语言来控制生物物理模型对全局数据集的应用-运行时支持构建可扩展和并行的解决方案，以解决涉及操纵不规则数据结构（如四叉树）的问题-并行I/O，特别是将大型阵列和四叉树映射到并行磁盘和磁盘系统上，并使用低开销的批量传输访问它们的新方法。开发工作将在安装在马里兰大学的32处理器连接机CM5和IBM SP1上进行，我们建议将其作为程序的一部分获得。该奖项由美国高级项目研究局以及美国国家科学基金会在地质、生物和计算机科学方面的项目提供支持。9318145 Messina大挑战应用小组竞赛为支持多学科科学家和工程师团队提供了一种机制，以实现1993财政年度高性能计算和通信（HPCC）计划的目标。理想的提案不仅提供了在(1)科学或工程的基本问题上取得重大进展的机会，其解决方案可以通过应用高性能计算技术和资源来推进，或者(2)促进这些进步的启用技术。而且科学和计算活动之间也有重要的相互作用，通常涉及数学、计算机或计算科学家，这将对高性能计算活动产生影响，超出特定的科学或工程问题领域或正在研究的学科。这个多学科的项目将研究和开发在计算科学和工程中有效实现I/O密集型应用的策略。可扩展的并行I/O方法将由一个由计算机科学家和应用科学家组成的团队来追求，他们将共同努力：*抽象并定义I/O模型（模板）*定义用于高效并行I/O的应用级方法*在大型计算机上实现和测试应用级I/O工具。Pablo性能分析环境将为性能检测和分析提供基础。应用程序已经在先进的体系结构系统上完全运行，它们的作者都是这个项目的共同研究者。主要使用的计算机将是加州理工学院的英特尔Touchstone Delta和Paragon系统，每台系统都有超过500个计算节点。五个应用领域将包括：流体动力学、化学、天文学、神经科学和材料处理等离子体的建模。这些应用程序的并行程序涵盖了一系列I/O模式和容量，本项目将开发的技术将与广泛的工程和科学应用相关。此外，通过克服当前的I/O限制，该奖项针对的特定应用将取得重大的新的科学和工程成果。到项目结束时，持续的teraFLOPS计算机将可用。该项目将使用当今先进的计算机设计和实现可扩展I/O的一般方法，立即应用这些方法在几个领域进行前所未有的应用，并使用