Introducing High-Performance Computing to Undergraduate Students
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© American Society for Engineering Education, 2016. Recently, President Obama issued an Executive Order to ensure the United States' leadership in computing. Necessary hardware and software design skills should be introduced into university curricula. Computing has been advanced to High Performance Computing (HPC) throughout the past decades. However, undergraduate students are still lacking of experience in how HPC functions especially in minority-serving institutions, because our current computing curricula do not adequately cover HPC contents. To address this problem, a team of faculty members have obtained external funding supports to improve undergraduate computing education through enhanced courses and research opportunities. The goal is to incorporate HPC concepts and training across the computing curricula in multiple disciplines in order to motivate students' interests in computing and improve their problem-solving skills. This three-year project has already finished the second year of implementation. During the first year, a diverse teaching environment was established, including a HPC cluster and embedded HPC platforms. Both platforms supported students' learning and research in parallel programming, embedded systems design, and data cloud. In the second project year, several courses were revised or developed across three departments: Electrical and Computer Engineering, Computer Science, and Engineering Technology. New course materials integrating the parallel and distributed computing concepts were developed and offered to undergraduate students. Project-based learning was introduced into classroom. More advanced concepts, such as computer vision and machine learning were explored by undergraduate students. At the same time, the research results were disseminated in junior and senior level courses. Faculty members applied effective pedagogy to teach new generation computing. For all the classes involved in this project, student surveys were collected to guide future project implementation. This article shares the current outcomes and findings of the project.
author list (cited authors)
Cui, S., Wang, Y., Li, L., Peng, X., & Yalvac, B.