MRI: Acquisition of a HPC System: Computing for Sustainability

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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.