Undergraduate Summer Research in High-performance Computing with Engineering Applications: An Experience Report

Daqing Hou; Yu Liu

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Conference: 2020 ASEE Virtual Annual Conference Content Access
Location: Virtual On line
Publication Date: June 22, 2020
Start Date: June 22, 2020
End Date: June 26, 2021
Conference Session: Computing and Information Technology Division Technical Session 3
Tagged Division: Computing and Information Technology
Tagged Topic: Diversity
Page Count: 12
DOI: 10.18260/1-2--35416
Permanent URL: https://peer.asee.org/35416
Download Count: 388

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Paper Authors

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Daqing Hou Clarkson University

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Dr. Daqing Hou is Professor and Director of Software Engineering in Department of Electrical and Computer Engineering at Clarkson University, Potsdam, New York. His research interests include Software Engineering, Engineering Education, Cyber Security, and Smart Energy.

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Yu Liu Clarkson University

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Dr. Yu Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at Clarkson University. Prior to joining Clarkson University, he was a research scientist at the Canadian Nuclear Laboratories (CNL) from 2013 through 2017. In addition, he was employed at Motorola as a senior software engineer from 2003 through 2007, and IBM from 2011 through 2013. He received his B.S. and M.S. degrees from Sichuan University, China in 2000 and 2003, respectively, and his Ph.D. degree from Southern Illinois University Carbondale in 2011. His research interests include high-performance computing, computer architectures, real-time systems, and wireless sensor networks. He has published over 30 peer-reviewed research papers.

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Abstract

High Performance Computing (HPC) stands at the forefront of engineering innovation. With affordable and advanced HPC resources more readily accessible than ever before, computational simulation of complex physical phenomena becomes an increasingly attractive strategy to predict the physical behavior of diverse engineered systems. Furthermore, novel applications of HPC in engineering are highly interdisciplinary, requiring advanced skills in mathematical modeling, algorithm development as well as programming skills for parallel, distributed and concurrent architectures and environments. This and other possible reasons have created a shortage of qualified workforce to conduct the much-needed research and development in these areas. This paper describes our experience with mentoring a cohort of ten high achieving undergraduate students in Summer 2019 to conduct engineering HPC research for ten weeks in X University. Our mentoring activity was informed and motivated by an initial informal study with the goal to learn the roles and status of HPC in engineering research and what can be improved to make more effective use of it. Through a combination of email surveys, in-person interviews, and a manual analysis of faculty research profiles in X University, we learn several lessons. First, a large proportion of the engineering faculty conducts research that is highly mathematical and computational and driven by disciplinary sciences, where simulation and HPC are widely needed as solutions. Second, due to the lack of resources to provide the necessary training in software development to their students, the interviewed engineering groups are limited in their ability to fully leveraging HPC capability in their research. Therefore, novel pathways for training and educating engineering researchers in HPC software development must be explored in order to further advance the engineering research capability in HPC. With a multi-year support from NSF, our summer research mentoring activities were able to accommodate ten high-achieving undergraduate students recruited from across the USA and their faculty mentors on the theme of HPC applications in engineering research. We describe the processes of students recruitment and selection, training and engagement, research mentoring, and professional development for the students. Best practices and lessons learned are identified and summarized based on our own observations and the evaluation conducted by an independent evaluator. In particular, improvements are being planned so as to deliver a more wholistic and rigorous research experience for future cohorts.

Citation
Format

Hou, D., & Liu, Y. (2020, June), Undergraduate Summer Research in High-performance Computing with Engineering Applications: An Experience Report Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35416

TY  - CPAPER
AB  - High Performance Computing (HPC) stands at the forefront of engineering innovation. With affordable and advanced HPC resources more readily accessible than ever before, computational simulation of complex physical phenomena becomes an increasingly attractive strategy to predict the physical behavior of diverse engineered systems. Furthermore, novel applications of HPC in engineering are highly interdisciplinary, requiring advanced skills in mathematical modeling, algorithm development as well as programming skills for parallel, distributed and concurrent architectures and environments. This and other possible reasons have created a shortage of qualified workforce to conduct the much-needed research and development in these areas. This paper describes our experience with mentoring a cohort of ten high achieving undergraduate students in Summer 2019  to conduct engineering HPC research for ten weeks in X University.  Our mentoring activity was informed and motivated by an initial informal study with the goal to learn the roles and status of HPC in engineering research and what can be improved to make more effective use of it. Through a combination of email surveys, in-person interviews, and a manual analysis of faculty research profiles in X University, we learn several lessons. First, a large proportion of the engineering faculty conducts research that is highly mathematical and computational and driven by disciplinary sciences, where simulation and HPC are widely needed as solutions. Second, due to the lack of resources to provide the necessary training in software development to their students, the interviewed engineering groups are limited in their ability to fully leveraging HPC capability in their research.  Therefore, novel pathways for training and educating engineering researchers in HPC software development must be explored in order to further advance the engineering research capability in HPC.  With a multi-year support from NSF, our summer research mentoring activities were able to accommodate ten high-achieving undergraduate students recruited from across the USA and their faculty mentors on the theme of HPC applications in engineering research. We describe the processes of students recruitment and selection, training and engagement, research mentoring, and professional development for the students. Best practices and lessons learned are identified and summarized based on our own observations and the evaluation conducted by an independent evaluator.  In particular, improvements are being planned so as to deliver a more wholistic and rigorous research experience for future cohorts.
AU  - Daqing Hou
AU  - Yu Liu
CY  - Virtual On line 
DA  - 2020/06/22
PB  - ASEE Conferences
TI  - Undergraduate Summer Research in High-performance Computing with Engineering Applications: An Experience Report
UR  - https://peer.asee.org/35416
DO  - 10.18260/1-2--35416
ER  -