MRI: Acquisition of a HPC System: Computing for Sustainability

该项目获得了一个新的高性能计算(HPC)平台，旨在加速知识发现，提供外部可见性，并帮助解决国家需求和社会效益问题，同时支持来自6所大学20个系的约30名研究人员的研究。这项工作建立在科学家的专业知识和机构对模拟和数据驱动科学的关注基础上，以创建能够在以下四个领域取得进展的计算基础设施：-可持续能源：新的HPC集群支持高通量分析，帮助确定未来技术(如风能、太阳能和生物能源)，同时作为催化、电池、2D材料和有机电子领域的计算材料研究的关键平台，用于虚拟勘探设计和控制。-数字农业：该机构强调用于生物可再生生产的微生物，强调重要谷类作物(例如玉米、大麦和大豆)基因组进步的生物技术的植物科学研究、表型预测、精准农业、气候科学和耕作实践的可持续性。因此，研究工作跨越微生物、植物和动物物种，所有这些都变得越来越受数据驱动。-可持续医疗保健：HPC平台支持纳米颗粒合成和定向药物输送机制方面的基本医疗保健应用，识别阿尔茨海默氏症和帕金森病的生物标记物，以及为可持续制药应用建立多相流物理模型。该机构的生物医学计划涵盖兽医、科学、人文科学和工程学院。-HPC研究和培训：基础设施使培训活动得以继续，为全球参与HPC意识的劳动力做好准备。正在开发硬件、软件和培训方法，以设计强大、全面、开放、科学驱动、用户友好的网络基础设施，由具有处理能力的标准化和精选的感兴趣的数据集组成。更广泛的影响：这项建议解决了三大类更广泛的影响：-向更广泛的研究社区提供计算算法作为开源代码，使其能够对能源、食品、医疗保健和基础设施设计方面的可持续发展努力产生广泛的影响(国家和社会)；-通过丰富现有的研究基础设施，将HPC纳入高级课程，以培训本科生、研究生和博士后研究员计算建模和算法开发，从而加强和促进新的合作努力；以及-向主要是本科生的机构提供时间，并制定积极的招聘计划，以吸引女性、代表性不足的少数族裔和第一代学生进入该机构。这些目标将与两个国家科学基金会奖项一起实现：红色骑行和S_STEM ECSEL。

This project, acquiring a new high performance computing (HPC) platform, aims to accelerate knowledge discovery, to provide external visibility, and to help problems of national need and societal benefit while supporting research from approximately 30 investigators from 20 departments in 6 colleges. The work builds on the expertise of scientists and the institutional focus on simulation- and data-driven science to create computing infrastructure that enables advances in the following four areas:- Sustainable Energy: The new HPC cluster enables high throughput analysis and helps identify future technologies (such as wind, solar, and bioenergy) while serving as the key platform for computational materials research in catalysis, batteries, 2D materials and organic electronics for virtual exploration design and control. - Digital Agriculture: The institution emphasizes microbial organisms for bio-renewable production, plant science research emphasizing biotechnology of important cereal crops (e.g., maize, barley, and soybeans) genomic advances, phenotypic prediction, precision agriculture, climate sciences, and sustainability of farming practices. Thus the research efforts span microbial, plant, and animal species, all of which are becoming more and more data driven.- Sustainable Healthcare: The HPC platform supports (with data-driven approaches for translational health) basic applications to health care in nanoparticle synthesis and targeted drug delivery mechanisms, identification of biomarkers for Alzheimer's and Parkinson's diseases, and modeling of multi-phase flow physics for sustainable pharmaceutical applications. The institution's biomedical program spans veterinary medicine, sciences, human sciences, and engineering schools.- HPC Research and Training: The infrastructure enables continuation of training activities to prepare a globally-engaged HPC-aware workforce. Hardware, software, and training methods are under development to design robust, comprehensive, open, science-driven, user-friendly cyberinfrastructure consisting of standardized and curated datasets of interest with processing capabilities. Broader Impacts:This proposal addresses three main classes of broader impacts:- Availability of computational algorithms to the broader research community as open-source codes, enables broad impact (national and societal) on sustainability efforts in energy, food, healthcare, and infrastructure design;- Enhancing and enabling new collaborative efforts by enriching the current research infrastructure that incorporates HPC into advanced course to train undergraduates and graduate students and postdoctoral fellows in computational modeling and algorithm development; and- Availability of time to primarily undergraduate institutions coupled with active recruitment plans to attract women, underrepresented minorities, and first generation students to the institution. These goals will be achieved in conjunction with two NSF awards: RED RIDE and S_STEM ECSEL.