Multidisciplinary Education on Big Data + HPC + Atmospheric Sciences

Wang, Jianwu; Gobbert, Matthias K.; Zhang, Zhibo; Gangopadhyay, Aryya; Page, Glenn G.

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Date

2017-11-01

Type of Work

8 pages
Text
conference paper preprint

Citation of Original Publication

Wang Jianwu, Gobbert K. Matthias, Zhang Zhibo, Gangopadhyay Aryya, Page Glenn, Multidisciplinary Education on Big Data + HPC + Atmospheric Sciences, Proceedings of the Workshop on Education for High-Performance Computing (EduHPC-17) Proceedings of the Workshop on Education for High-Performance Computing (EduHPC-17), 2017

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This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.

Subjects

Big Data
High-Performance Computing
Atmospheric Sciences
Multidisciplinary Education
Developmental Evaluation
High Performance Computing Facilty (HPCF)

Abstract

We present a new initiative to create a training program or graduate-level course (cybertraining.umbc.edu) in big data applied to atmospheric sciences as application area and using high-performance computing as indispensable tool. The training consists of instruction in all three areas of "Big Data + HPC + Atmospheric Sciences" supported by teaching assistants and followed by faculty-guided project research in a multidisciplinary team of participants from each area. Participating graduate students, post-docs, and junior faculty from around the nation will be exposed to multidisciplinary research and have the opportunity for significant career impact. The paper discusses the challenges, proposed solutions, practical issues of the initiative, and how to integrate high-quality developmental program evaluation into the improvement of the initiative from the start to aid in ongoing development of the program.