MRI: Acquisition of Heterogeneous Computer System for Machine Learning

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This award supports the purchase, deployment, and operation of a heterogeneous computer system to advance the research interests of many faculty in the Stony Brook University's Artificial Intelligence research community. The shared research instrument will enable discovery in a multitude of areas. For example: in Geosciences, the cluster will be used to process satellite imagery to map remote parts of the Arctic and Antarctic; in Biosciences it will be employed to build neural networks that will advance cardiac imagery and fMRI research; in Social Sciences it will help produce methods and tools that can illuminate social and psychological determinants of population health. The provisioning of the instrument in the Stony Brook University campus will greatly benefit hundreds of graduate and undergraduate students taking courses in machine learning and artificial intelligence each year. The proposed cluster will offer professionally-managed resources providing a standardized environment with adequate technical support. Further, student demand is anticipated to continue to grow through several ongoing initiatives including an undergraduate CS concentration in artificial intelligence, with new courses in NLP and data science, a recently approved graduate CS concentration in Data Science, and a proposed "Data Science+X" undergraduate sequence integrating with several majors in the College of Arts and Sciences (CAS).The cluster will comprise of three categories of nodes: (1) a large Graphics Processing Unit (GPU) machine, (2) GPU server machines with large amounts of memory and (3) Field Programmable Gate Arrays (FPGA) machines thus providing a forward-looking computing environment focused on supporting research on and enabled by AI. It will constitute the research instrumentation catalyst for the Institute for AI-Driven Discovery and Innovation (AI Institute) and significantly overhaul the compute capability of the institution. This system?s heterogeneity will allow for a more versatile shared environment with excellent performance. will support research in three directions: 1) Artificial Intelligence (AI) including Natural Language Processing, Computer Vision, and Machine Learning (ML) 2) applications of AI and ML on a variety of scientific disciplines including Biomedical Informatics, Chemistry, Ecology, and Linguistics, 3) Computer Science (CS) research on HPC such as visualization, neural network compilation, and process scheduling. Furthermore, the strong educational and outreach activities that engage high school students and teachers, as well as undergraduate and graduate students have the potential to support the building of a skilled workforce of developers, researchers, staff and users.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.