MRI: Acquisition of a GPU-Based Cloud Infrastructure for Inter-/Multi-Disciplinary Research and Education at a Primarily Undergraduate Institution

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This project, acquiring equipment to establish a GPU-based cloud, aims to enable big data related interdisciplinary projects, specifically collaborative research projects in computer science, large-scale medical data, computational chemistry, and geology. These include:- Intelligent Internet of Things (IoT),- Smart Health,- Spatial Computing, and - Computational ChemistryThe intelligent IOT research would utilize the infrastructure to develop new deep learning models to enable smart living and navigation for vision impaired people. The big data enriched health research expects to find effective solutions to solve problems of obesity and non-communicable chronic diseases, serious threats to public health in the US and globally, using the instrumentation to compute the models with enormous health data. The geoscience research would enabled the establishment of "American Spatial Data Portal" (ASDP) that will provide a central repository of spatial data to expedite research on geospatial data mining and applications. A cloud geospatial education system would be developed on the instrument to transform the nation's geoscience education. The computational chemistry research would take advantage of the computation capability of the cloud to discover, design, and evaluate new and low costs catalysts for important chemical reactions, which could significantly change the life of the world. This GPU-based cloud is expected to facilitate the data and computation intensive research progress across many disciplines not only at this mainly undergraduate university, but also at other institutions through authorized and scheduled remote access. Furthermore, the infrastructure would be shared via high speed internet to other colleagues in the nation, and to international collaborators who are interested. Broader Impacts: By involving students in the activities of installation, configuration, and instrumentation, this project would provide valuable opportunities to train future scientists, engineers, and instrumentalists. The developed new cross-list courses and summer training program would train hundreds of both senior and graduate students on GPU and big data related knowledge and skills. Moreover, due to the appropriate mentoring that the investigators are able to offer, overall students and minorities can benefit.