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REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering
NSF
About This Grant
The project is a renewal of the Research Experiences for Undergraduates (REU) EXERCISE (Explore Emerging Computing in Science and Engineering) site at Salisbury University (SU) for the next three years. EXERCISE is an interdisciplinary project that explores emerging paradigms in parallel computing with data and compute intensive applications in science and engineering. The project will advance the field of high-performance computing and foster a “parallel thinking” mindset for problem solving among the current generation students. The REU site will provide thirty undergraduates with a unique opportunity to conduct research and present their findings at regional and national professional conferences. The site will also prepare undergraduate participants for their future graduate studies and professional careers. The project will provide parallel computing resources to educational and research communities, including primarily undergraduate institutions (PUIs) with limited access to high performance computing facilities and curricula. The renewal site will continue to attract a motivated and diverse student body, including those from local historically black colleges and universities (HBCUs) and community colleges on Maryland’s Eastern Shore, into computational science and engineering majors and the broader Science, Technology, Engineering, and Mathematics (STEM) fields. Overall, the project has the potential to contribute to workforce development and economic growth in Maryland’s Eastern Shore, a rural coastal region. The EXERCISE project will introduce parallel computing concepts to undergraduate students through foundational parallel programming models and low-cost parallel systems, applied in diverse research projects. The goal of the proposed research is to provide students with knowledge and hands-on experience in developing parallel algorithms and programs, as well as in investigating the performance improvement and computational limitations of parallel processing. In this project, students will have opportunities to explore concurrent software and multiprocessor architectures, design efficient parallel algorithms, and apply emerging parallel computing techniques to address real-world challenges in areas such as pattern recognition and machine learning, public health and global epidemics, sustainable aquaculture farming, human activity recognition, flood detection, and smart transportation. The project consists of two components: an online pre-program workshop held each spring and an on-site research program conducted every summer. The host institution will collaborate with the University of Maryland Eastern Shore, an HBCU, and the University of Maryland College Park to provide multi-disciplinary faculty expertise and a variety of summer activities. 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.
Focus Areas
Eligibility
How to Apply
Up to $447K
2028-01-31
One-time $749 fee · Includes AI drafting + templates + PDF export
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