Characteristic Science Applications for the Leadership Class Computing Facility

领先级计算设施的特色科学应用

• 批准号: 2139536
• 负责人: Daniel Stanzione
• 金额: $ 699.94万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2139536&HistoricalAwards=false
• 关键词: Characteristic; Science; Applications; Leadership; Class

The goal of this project is to select, study, and transform a set of Characteristic Science Applications (CSAs) to enable next-generation science on the NSF Leadership-Class Computing Facility (LCCF). The CSAs were chosen to represent a broad range of science domains and computational approaches, and each CSA will comprise one or more computer codes and a challenge problem to be solved on the LCCF. The set of CSAs will enable the project to verify the design of the LCCF and validate that the facility is applicable across the broad range of science disciplines supported by the NSF when it is constructed. Furthermore, the transformations made to the codes and workflows in the CSAs will provide best practice models and implementation exemplars that will inform training materials, tutorials, and other educational content. This will ensure that the nation's science and engineering research community will be effective on the LCCF from day one of operations.The project plans to evaluate a broad selection of science applications and challenge problems, laying the foundations for a transformation of the computer codes in a way that will support the LCCF broad goal of enabling a ten-fold or more time to solution performance improvement over NSF's current leadership computing resource, Frontera. This capability improvement will come from a combination of increased scale of the LCCF primary computing system(s), increased capabilities of the components (on-node I/O bandwidth, inter-node I/O bandwidth, disk and memory bandwidth, access speed, cores, etc.) that make up the computing instrument, and improvements in the software codes that make up the set of science applications used to demonstration ten-fold performance improvement.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目的是选择，研究和改变一组特征科学应用程序（CSA），以使NSF Leadership-Classive-Class计算机（LCCF）实现下一代科学。选择CSA代表广泛的科学领域和计算方法，每个CSA将构成一个或多个计算机代码，以及在LCCF上解决的挑战问题。 CSA的集合将使项目能够验证LCCF的设计，并验证该设施适用于NSF构建时NSF支持的广泛科学学科。 此外，对CSA中的代码和工作流进行的转换将提供最佳实践模型和实施典范，这些模型将为培训材料，教程和其他教育内容提供信息。 这将确保国家的科学和工程研究社区从运营的第一天开始在LCCF上有效。该项目计划评估广泛的科学应用和挑战问题，为计算机代码转换的基础，以支持LCCF的方式来支持LCCF的广泛目标，以使其在NSF当前的领导力资源中启用十倍或更多时间的时间来提高效果，以提高效果，以促进NSF的领导力资源，并供电。 This capability improvement will come from a combination of increased scale of the LCCF primary computing system(s), increased capabilities of the components (on-node I/O bandwidth, inter-node I/O bandwidth, disk and memory bandwidth, access speed, cores, etc.) that make up the computing instrument, and improvements in the software codes that make up the set of science applications used to demonstration ten-fold performance improvement.This award reflects NSF的法定使命，并使用基金会的知识分子优点和更广泛的影响审查标准来评估值得支持。