A Study on the Knowledge Elements of HPC in Computational Science through Analysis of Educational Needs

교육요구분석을 통한 계산과학분야의 고성능컴퓨팅 지식요소에 관한 연구

  • Yoon, Heejun (Dept. of Disciplinary Education, Sungkyunkwan University) ;
  • Ahn, Seongjin (Dept. of Computer Education, Sungkyunkwan University)
  • 윤희준 (성균관대학교 교과교육학과) ;
  • 안성진 (성균관대학교 컴퓨터교육과)
  • Received : 2018.10.16
  • Accepted : 2018.10.25
  • Published : 2018.10.31


The purpose of this study is to suggest the knowledge elements for HPC education in computational science. For this purpose, the survey for HPC experts was conducted to verify the content validity and reliability, and the 20 candidate knowledge elements was extracted. And the second survey for HPC users was conducted to apply the t test, Borich requirement, and The Locus for Focus model. And 10 knowledge elements for HPC education were derived. As a result, the first group was 'Parallelism Fundamentals', 'Parallelism', 'Parallel communication and coordination', 'Parallel Decomposition', 'Parallel Algorithms, Analysis, and Programming' and 'Introduction to Modeling and Simulation', 'Fundamental Programming Concepts', 'Fundamental Data Structures', 'Memory Management', 'Algorithms and Design' were second group for HPC education.


  1. Stevenson, D. E. (1993, March). Science, computational science, and computer science: at a crossroads. In Proceedings of the 1993 ACM conference on Computer science (pp. 7-14). ACM.
  2. Education, S. W. G. O. C. (2001). Graduate education in computational science and engineering. SIAM Review, 43(1), 163-177.
  3. Reed, D. A., Bajcsy, R., Fernandez, M. A., Griffiths, J. M., Mott, R. D., Dongarra, J., ... & Ponick, T. L. (2005). Computational science: Ensuring America's competitiveness. PRESIDENT'S INFORMATION TECHNOLOGY ADVISORY COMMITTEE ARLINGTON VA.
  4. Bo, L., Zhenliu, Z., & Xiangfeng, W. (2012, March). A survey of HPC Development. In Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on (Vol. 2, pp. 103-106). IEEE.
  5. National Academies of Sciences, Engineering, and Medicine. (2016). Future directions for NSF advanced computing infrastructure to support US science and engineering in 2017-2020. National Academies Press.
  6. P.L. 102-94 The High Performance Computing Act of 1991
  8. Van De Vanter, M. L., Post, D. E., & Zosel, M. E. (2005, May). HPC needs a tool strategy. In Proceedings of the second international workshop on Software engineering for high performance computing system applications (pp. 55-59). ACM.
  9. Zarestky, J., & Bangerth, W. (2014, November). Teaching High Performance Computing: Lessons from a flipped classroom, project-based course on finite element methods. In Proceedings of the Workshop on Education for High-Performance Computing (pp. 34-41). IEEE Press.
  10. Yasar, O., Rajasethupathy, K. S., Tuzun, R. E., McCoy, R. A., & Harkin, J. (2000). A new perspective on computational science education. Computing in Science & Engineering, 2(5), 74-79.
  11. Shephard, M. S., Smith, C., & Kolb, J. E. (2013). Bringing hpc to engineering innovation. Computing in Science & Engineering, 15(1), 16-25.
  12. ACM/IEEE-CS Joint Task Force on Computing Curricula, Computer Science Curricula 2013, ACM Press and IEEE Computer Society Press, December 2013
  13. Borich, G. D. (1980). A needs assessment model for conducting follow-up studies. Journal of teacher education, 31(3), 39-42.
  14. Jo, D. (2009). Exploring How to Set Priority in Need Analysis with Survey. A Journal of Research in Education, 35, 165-187.
  15. Gallopoulos, S., Houstis, E. N., & Rice, J. R. (1992). Future research directions in problem solving environments for computational science.
  16. Yasar, O., & Landau, R. H. (2003). Elements of computational science and engineering education. SIAM review, 45(4), 787-805.
  17. Fabricius, U., Freundl, C., Kostler, H., & Rude, U. (2005, May). High performance computing education for students in computational engineering. In International Conference on Computational Science (pp. 27-35). Springer, Berlin, Heidelberg.
  18. Squires, S., Van De Vanter, M., & Votta, L. (2006, February). Yes, There Is an "Expertise Gap" In HPC Applications Development. In Third Workshop on Productivity and Performance in High-End Computing (PPHEC06).
  19. Armosky, B., Brown, S., Drummond, T., Ferguson, J., Gerber, R., Hacker, T. J., ... & Traxler, K. (2007). HPC University. In TG08-TeraGrid Conference, Madison, WI.
  20. EDUCATION, S. W. G. O. C. U., Co-Chairs, P. T. A. L. P., Shiflet, A., Vakalis, I., Jordan, K., & John, S. S. (2011). Undergraduate computational science and engineering education. SIAM review, 53(3), 561-574.
  21. Sancho, M. R., Alexandrova, N., & Gonzalez, M. (2015, December). Addressing HPC skills shortages with parallel computing MOOC. In Interactive Collaborative and Blended Learning (ICBL), 2015 International Conference on (pp. 86-93). IEEE.
  22. Wilson, L. A., & Dey, S. C. (2016, November). Computational science education focused on future domain scientists. In Proceedings of the Workshop on Education for High Performance Computing (pp. 19-24). IEEE Press.
  23. Gordon, S. I., Demmel, J., Destefano, L., & Rivera, L. (2016). Implementing a Collaborative Online Course to Extend Access to HPC Skills. Computing in Science & Engineering, 18(1), 73-79.
  24. Cahill, K. J., Lathrop, S., & Gordon, S. (2017). Building a Community of Practice to Prepare the HPC Workforce. Procedia computer science, 108, 2131-2140
  25. Rüde, U., Willcox, K., McInnes, L. C., & Sterck, H. D. (2018). Research and education in computational science and engineering. Siam Review, 60(3), 707-754.
  26. SIAM,
  27. Park SunJu. (2017). Analysis of Learners' Preferences in SW Education Contents Development. Journal of the Korean Association of Information Education, 21(6), 691-699.
  28. Han Young Shin. (2018). Analysis of Effectiveness of Programming Learning for Non-science Major Preliminary Teachers' Development of Computational Thinking. Journal of the Korean Association of Information Education, 22(1), 41-52.
  29. Lawshe, C. H. (1975). A quantitative approach to content validity 1. Personnel psychology, 28(4), 563-575.
  30. Ayre, C., & Scally, A. J. (2014). Critical values for Lawshe's content validity ratio: revisiting the original methods of calculation. Measurement and Evaluation in Counseling and Development, 47(1), 79-86.
  31. Lee, J. E., & Kim, H. (2016). Analysis of College Students' Educational Needs for Career Education. Journal of Learner-Centered Curriculum and Instruction, 16, 1001-1027.