MRI: Acquisition of a Shared High-Performance Computing System for Cyber-Enabled System Design

MRI：获取用于网络支持系统设计的共享高性能计算系统

• 批准号: 2018594
• 负责人: Arun Somani
• 金额: $ 60万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018594&HistoricalAwards=false
• 关键词: MRI; Acquisition; Shared; Performance; Computing

This instrument, a new high-performance computing (HPC) platform, aims to accelerate knowledge discovery by supporting the research of 32 investigators from 15 departments. Building upon an institutional focus on simulation- and data-driven science, it will enable significant advances in two types of research, foundational and translational, and support training and development. Leveraging the HPC cluster, investigators in computer science, engineering, statistics, agriculture, and biology will conduct research on cyber-enabled systems design, thermal flows in the built environment, the design of materials, and phenotyping methods for plant and animal agriculture. This HPC cluster will enhance existing collaborative efforts and enable building new ones, support advanced student training in computational modeling and algorithm development, and allow sustained workforce development. This HPC system for Cyber-Enabled System Design includes a mix of computing nodes and nodes with general-purpose graphics processing units (GPGPUs), with sufficient memory, disk storage and parallel input/output capability to support cutting-edge research. The instrument will enable: (a) foundational data science advances with a focus on algorithms for system design under uncertainty, for cyber-physical data assimilation, and analysis of complex flow and material systems, (b) translation research in three thematic areas: energy, materials and manufacturing, and precision agriculture, with a focus on “materials by design”, smart power grid, quieter aircraft and wind turbines, and precision animal science, and (c) HPC training for undergraduate, graduate, and postgraduate students, to prepare a globally engaged, HPC aware workforce. Research using this computer system has the potential to improve food production, energy usage and manufacturing.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.

该仪器是一个新的高性能计算 (HPC) 平台，旨在通过支持来自 15 个部门的 32 名研究人员的研究来加速知识发现，它将在机构重点关注模拟和数据驱动科学的基础上实现重大进步。基础性和转化性两种类型的研究，并利用 HPC 集群支持培训和开发，计算机科学、工程、统计学、农业和生物学的研究人员将开展网络系统设计、建筑环境中的热流、材料的设计，该 HPC 集群将增强现有的协作工作并支持建立新的协作工作，支持计算建模和算法开发方面的高级学生培训，并实现持续的劳动力发展。计算节点和具有通用图形处理单元（GPGPU）的节点的组合，具有足够的内存、磁盘存储和并行输入/输出能力，以支持前沿研究：（a）基础数据科学的进步。专注于系统算法不确定性下的设计，用于网络物理数据同化以及复杂流动和材料系统的分析，(b) 三个主题领域的翻译研究：能源、材料和制造以及精准农业，重点是“材料设计”，智能电网、更安静的飞机和风力涡轮机以及精密动物科学，以及 (c) 为本科生、研究生和研究生提供 HPC 培训，以培养一支全球参与、具有 HPC 意识的劳动力 使用该计算机系统的研究有可能得到改善。粮食生产、能源使用和该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。