High Performance Computing for Land Cover Dynamics

土地覆盖动态的高性能计算

• 批准号: 9318183
• 负责人: Larry Davis
• 金额: $ 296.57万
• 依托单位: University of Maryland, College Park
• 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 2000-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9318183&HistoricalAwards=false
• 关键词: Performance; Computing; Land; Cover; Dynamics

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 hierarchical 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 sophisticate d 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 l/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.

9318183戴维斯大挑战应用程序组竞争提供了一种机制，支持科学家和工程师的多学科团队，以满足高性能计算和通信（HPCC）在1993财政年度的倡议的目标。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）科学或工程中的一个基本问题，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）促进这些进步的技术，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，这将对高性能计算活动产生影响，超出正在研究的特定科学或工程问题领域或学科。研究人员将研究高性能并行计算在遥感中一类科学上重要和计算要求高的问题中的应用-土地覆盖动态问题，包括为全球碳循环，水文模拟和全球生态对气候变化和人类活动的响应生成改进的精细空间分辨率数据。这项研究是合作的，包括来自马里兰州大学，印第安纳州大学，新罕布什尔大学和美国宇航局戈达德航天中心的科学家。该奖项将结合联合收割机的研究， - 新的遥感数据分析程序 - 多光谱、多分辨率和 多时相 将数据集映射到统一全局数据结构中 基于 分层数据结构（即，四叉树） - 利用这些分层并行数据 structures for the 空间数据（地图和产品）的表示 从图像发展 分析）和建立空间数据库 系统与 科学家可以使用的简化的查询语言， 控制 将生物物理模型应用于全球数据集 - 运行时支持构建可扩展的和 并行解决方案 涉及操纵不规则数据的问题 等结构 作为四叉树 - 并行I/O，特别是用于映射大型 阵列和 四叉树到并行磁盘和磁盘系统上， 访问它们 开发工作将在32处理器上进行 连接机CM 5，安装在大学 马里兰州，并在IBM SP1，我们建议获得作为 计划的一部分。 该奖项得到了 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。