MRI: Acquisition of High Performance Computing System for Interdisciplinary Research and Teaching

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This proposal aims to acquire a high-performance computing (HPC) cluster to support research and training in the sciences. Claiming that high performance computation is playing and increasingly significant role in nearly every facet of modern society, the institution aims to facilitate the incorporation of high-performance computing into undergraduate work across the liberal arts following its tradition of working very closely with its liberal arts students. Claiming that high performance computation plays an increasingly significant role in nearly every facet of the modern society and that research impacts extend beyond applications in STEM fields (e.g., impacting applications such as AI (Artificial Intelligence) and ML (Machine Learning), the institution would like to train students in pertinent areas that that make use of such general-purpose clusters. Both CPU and GPU computing nodes will help new users. The institution will implement support services to help users of many backgrounds in the use of the system. They expect the system’s generality and flexibility will facilitate the process in various fields (e.g.: Biology, Chemistry, Computer Science, Neurosciences).Training students in the use of the HPC technology should prepare the next generation of researchers. The new cluster will increase the capacity for leading edge research in STEM and facilitate recruitment of promising faculty candidates who seek to integrate research, training, and teaching in a liberal arts environment. The generality of the instrumentation supports collaboration and provides opportunities to explore more. Likely, many programs will utilize the cluster, contributing to the Undergraduate Fellows Program.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.