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Introducing High-Performance Computing to Undergraduate Students

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Software and Programming

Tagged Division

Computers in Education

Tagged Topic

Diversity

Page Count

11

DOI

10.18260/p.25453

Permanent URL

https://peer.asee.org/25453

Download Count

186

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Paper Authors

biography

Suxia Cui Prairie View A&M University

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Suxia Cui is an associate professor in the Department of Electrical and Computer Engineering at Prairie View A&M University (PVAMU). She joined PVAMU right after she obtained her Ph.D. degree in Computer Engineering from Mississippi State University in 2003. Her research interests include image and video processing, data compression, wavelets, computer vision, remote sensing, and computing education. Her projects are currently funded by NSF, United States Department of Agriculture, and Department of Education.

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Yonghui Wang Prairie View A&M University

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Dr. Yonghui Wang received his B.S. in Optoelectronics from Xidian University in 1993, his M.S. in electrical engineering from Beijing Polytechnic University in 1999; and his Ph.D. in computer engineering from Mississippi State University in 2003. From 1993 to 1996, he was a Research Engineer with the 41st Electrical Research Institute in Bengbu, China. From July 1999 to December 1999, he worked as an IT Specialist in IBM China, Beijing, China. From 2000 to 2003, he was a research assistant with the Visualization, Analysis, and Imaging Laboratory (VAIL), the GeoResources Institute (GRI), Mississippi State University. He is currently an Associate Professor with the Department of Engineering Technology, Prairie View A&M University. His research interests include digital signal processing, image and video coding, and wavelets.

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Lin Li Prairie View A&M University

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Lin Li is an associate professor of the Computer Science Department at Prairie View A&M University. He received his Ph.D. in computer science from the University of Nebraska at Lincoln in 2004. Before that, he received his B.S. and M.E. from Beijing Institute of Technology and Chinese Academy of Sciences in 1996 and 1999, respectively. His research interests are in Computer Networks, Machine Learning, and Computer Science Education.

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Xiaobo Peng Prairie View A&M University

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Associate Professor, Department of Mechanical Engineering, Prairie View A&M University

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Bugrahan Yalvac Texas A&M University

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Bugrahan Yalvac is an associate professor of science and engineering education in the Department of Teaching, Learning, and Culture at Texas A&M University, College Station. He received his Ph.D. in science education at the Pennsylvania State University in 2005. Prior to his current position, he worked as a learning scientist for the VaNTH Engineering Research Center at Northwestern University for three years. Yalvac’s research is in STEM education, 21st century skills, and design and evaluation of learning environments informed by the How People Learn framework.

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Abstract

Recently, present Obama issued an Executive Order to ensure the United States’ leadership in computing. Computing has been advanced to High Performance Computing (HPC) in the past decades, necessary skills including both hardware and software design should be introduced into university curricula. However, undergraduate students are still lacking of experience in how HPC functions, because our current computing curricula do not adequately cover HPC contents. To solve this problem, a team of faculty members obtained external funding aiming at improving undergraduate computing education through enhanced courses and research opportunities in a minority-serving institution. The goal was to incorporate HPC concepts and training across the computing curricula in multiple disciplines in order to motivate students’ interests in computing and improve their computing problem-solving skills, thus strengthening and diversifying the future U.S. workforce. This three year project already finished the second year of implementation. During the first year, a diverse environment was established with HPC cluster and embedded HPC platforms. Both platforms supported students’ research projects in parallel programming, embedded systems design, and data cloud. In the second project year, several courses has been revised or developed across three departments: Electrical and Computer Engineering, Computer Science, and Engineering Technology. New course materials integrating parallel and distributed computing concepts were developed and offered to undergraduate students. Project-based learning skill was introduced into the classroom. More advanced concepts, such as computer vision and machine learning were able to be explored in undergraduate research. At the same time, the research results were disseminated in junior and senior level courses. Furthermore faculty members are considering effective pedagogy to teach new generation computing. Evidence-based approaches were applied into one of the computing courses. For all the classes involved in this project, class surveys were collected to guide future development. This article shares the current outcomes and findings of the project.

Cui, S., & Wang, Y., & Li, L., & Peng, X., & Yalvac, B. (2016, June), Introducing High-Performance Computing to Undergraduate Students Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25453

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