REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering

Salisbury University, Salisbury MD

Investigators

Abstract

This award renews the EXERCISE Research Experiences for Undergraduates (REU) Site at Salisbury University, Maryland. The intellectual focus of the site is research on emerging paradigms in parallel computing. The Principal Investigator, together with mentors, will supervise a 10-week REU program that gives a diverse cohort of students a taste of computational thinking in the domain of parallel computing and also an understanding of the graduate school experience. The projects cover a breadth of areas in parallel computing and the students will gain experience in all aspects of research. The emphasis on parallel computing is important particularly at a time when multicore and multiprocessor architectures are becoming ubiquitous and more and more applications are utilizing parallelism. To ensure diversity, students will be selected from within Salisbury University as well as from regional community colleges, University of Maryland Eastern Shore and other Historically Black Colleges and Universities. Because of the ubiquity of multicore and multiprocessor architectures, parallel computing has become an important area of research in computing science. However, parallel computing brings with it several challenges. There are fundamental difficulties in program semantics related to process interleaving: a parallel program can yield inconsistent answers, or even crash, due to unpredictable interactions between simultaneous tasks. Secondly, communication, memory access, and I/O overhead may result in run-time delays. Finally, it is difficult to ensure that programs consume resources in a manner that simultaneously achieves efficiency and meets performance goals. Based on the above challenges, the REU Site will focus on four aspects of parallel computing, namely, algorithms, software, architecture and applications. Students will work with faculty mentors in completing cutting-edge research projects to tackle data and compute intensive applications that emphasize the above four aspects. By the end of program, students will acquire valuable skills, gain a broader and deeper understanding of research, and develop greater confidence in their abilities. In particular, they will be exposed to emerging paradigms in parallel computing such as MapReduce and GPU computing, and will have opportunities to explore concurrent software and multiprocessor architectures, and design efficient parallel algorithms, and to tackle data and compute intensive problems in computer and social networks, image and signal processing, and geographic information systems.