Seattle, Washington
June 14, 2015
June 14, 2015
June 17, 2015
978-0-692-50180-1
2153-5965
Systems Engineering
Diversity
11
26.652.1 - 26.652.11
10.18260/p.23990
https://peer.asee.org/23990
504
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. 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 the NSF, the United States Department of Agriculture, and the Department of Education.
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 Educational Technologies.
Lei Huang is an assistant professor in the Computer Science department at Prairie View A&M University. He received his Ph.D. in computer science from University of Houston in 2006, and his M.S. in computer science from Southwest Jiaotong University, China in 1997. His research areas are in High Performance Computing, Cloud Computing, Big Data Analytics, programming models and compiler optimizations.
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.
Enhance Computing Curricula with High Performance Computing Teaching and ResearchAbstractToday’s scientists and engineers depend increasingly on information and tools made availablethrough new advanced computing technologies, such as networks, large data analysis, andsophisticated simulation tools that assist in the understanding of natural phenomena. HighPerformance Computing (HPC) now plays a critical role in enabling such scientific andengineering inquiry. However, undergraduate students are still lacking of experience in howHPC functions, because our current computing curricula do not adequately cover HPC. To solvethis problem, a team of faculty members obtained external funding to improve undergraduatecomputing education through enhanced courses and research opportunities. The goal is toincorporate HPC concepts and training across the computing curricula in multiple disciplines inorder to motivate students’ interests in computing and strengthen their computing problem-solving skills, thus strengthening and diversifying the future U.S. workforce. The objectivesinclude: (a) Establish a platform to promote multidisciplinary research collaborations on computing hardware and software design; (b) Revamp core courses and corresponding labs, and develop new multidisciplinary courses, to incorporate HPC; (c) Develop faculty expertise as well as train undergraduate students with HPC through research and teaching initiatives; (d) Disseminate results for academic community and general public aiming at recruiting more students to computing disciplines.This is a collaborating project with three participating departments: Electrical and ComputerEngineering, Computer Science, and Engineering Technology. After the first project year, adiverse environment was established with HPC cluster and embedded HPC platforms. Bothplatforms supported students' research projects in parallel programming, embedded systemsdesign, and data cloud. In the past year, the project was successfully introduced in undergraduateclasses. New course materials integrating parallel and distributed computing concepts weredeveloped and offered to undergraduate students. Class surveys were collected to guide futuredevelopment. Based on the results, more courses will be renovated to accommodate HPCcontents in the coming years. A project-based learning scheme will also be introduced to our newcourse design and implementation including subjects like Computer Vision and MachineLearning. This article presents the current outcomes and findings of the project and a detailedplan of the ongoing education and research activities.
Cui, S., & Li, L., & Huang, L., & Wang, Y. (2015, June), Enhance Computing Curricula with High-Performance Computing Teaching and Research Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23990
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