CISE Postdoctoral Program: Postdoctoral Research Associate in Computational Science & Engineering Science: High Performance Computing for Remote Sensing Applications

CISE博士后项目：计算科学博士后研究员

• 批准号: 9625668
• 负责人: Larry Davis
• 金额: $ 4.62万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-03-15 至 1998-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9625668&HistoricalAwards=false
• 关键词: CISE; Postdoctoral; Program; Research; Associate

9625668 Davis, Larry University of Maryland, College Park CISE Postdoctoral Program: Postdoctoral Research Associate in Computational Science & Engineering Science: High Performance Computing for Remote Sensing Applications This award supports CES associate David Bader. The main objective of the proposed training and research plan is to develop innovative computational methods and software for applying high performance computing to fundamental problems arising in the analysis of remotely sensed image data. This work will be conducted at the University of Maryland Institute for Advanced Computer Studies (UMIACS) in close cooperation with Professor Davis (Computer Science), Goward (Geography), Ja'Ja' (Electrical Engineering), and Townshend (Geography), who are pursuing a number of closely related efforts. The application to be developed is a high performance system for estimating net primary production (NPP) using the production efficiency model (PEM) developed at the University of Maryland. The overall aim is to build a family of software modules that make use of a variety of algorithms to carry out geometric correction of images, to eliminate signals from extraneous sources (e.g. atmospheric correction), to sample spatially and temporally, and to generate derived geophysical properties. The modules will be constructed using proven portable and practical high performance programming languages and libraries. Our applications development will be conducted on two high performance computing platforms at UMIACS; a 16-node IBM SP-2 and a Digital Alpha cluster consisting of 40 Alpha processors networked via a Digital ATM Gigaswitch. The Maryland facility has approximately 300GB of online disk storage and a multi-terabyte tertiary storage system. ***

9625668戴维斯，马里兰州拉里大学，大学公园CISE博士后计划：计算科学与工程科学博士后研究助理：遥感应用程序的高性能计算该奖项支持CES Associate David Bader。 拟议的培训和研究计划的主要目的是开发创新的计算方法和软件，以将高性能计算应用于分析远程感知的图像数据时产生的基本问题。 这项工作将与马里兰大学高级计算机研究研究所（UMIACS）与戴维斯教授（计算机科学），高瓦德（GOWARD）（地理），Ja'ja'（电气工程）和Townshend（地理）密切合作，他们正在追求许多密切相关的工作。 要开发的应用程序是使用马里兰大学开发的生产效率模型（PEM）估算净初级生产（NPP）的高性能系统。 总体目的是建立一个软件模块系列，该软件模块使用各种算法来进行图像的几何校正，以消除来自外部源的信号（例如大气校正），以空间和时间上的样本以及产生派生的地球物理特性。 这些模块将使用经过验证的便携式和实用的高性能编程语言和库来构建。 我们的应用开发将在UMIACS的两个高性能计算平台上进行；一个16节点的IBM SP-2和一个数字Alpha群集，该群集由40个通过数字ATM Gigaswitch网络的Alpha处理器组成。 马里兰州的设施大约有300GB的在线磁盘存储和一个多型三级存储系统。 ***