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.

该工具是一种新的高性能计算（HPC）平台，旨在通过支持15个部门的32名研究人员的研究来加速知识发现。在机构关注模拟和数据驱动的科学的基础上，它将在两种类型的研究，基础和翻译以及支持培训和发展的两种类型的研究中取得重大进展。利用HPC群集，计算机科学，工程，统计，农业和生物学领域的研究人员将对支持网络的系统设计，建筑环境中的热流，材料设计以及动植物农业的表型方法进行研究。该HPC群集将增强现有的协作努力，并使建立新的协作，支持计算建模和算法开发的高级学生培训，并允许持续的劳动力发展。这种用于网络支持系统设计的HPC系统包括与通用图形处理单元（GPGPU）的计算节点和节点的混合，具有足够的内存，磁盘存储和并行输入/输出能力，以支持切割边缘研究。 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接受本科，研究生和研究生的培训，以准备全球参与的HPC Aware Forkce。使用该计算机系统的研究有可能改善粮食生产，能源使用和制造。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响评估标准来评估值得支持。