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A Study on Knowledge Unit for High-Performance Computing in Computational Science

계산과학분야의 고성능컴퓨팅에 관한 지식단위 연구

  • Yoon, Heejun (Department of Disciplinary Education, Sungkyunkwan University) ;
  • Ahn, Seongjin (Department of Computer Education, Sungkyunkwan University)
  • 윤희준 (성균관대학교 교과교육학과) ;
  • 안성진 (성균관대학교 컴퓨터교육학과)
  • Received : 2018.04.25
  • Accepted : 2018.05.25
  • Published : 2018.05.31

Abstract

Computational science is at an early stage and is not yet fully active, and the high-performance computing required in the field of computational science is at present a special subject of parallel and distributed computing in computer science. Additionally, there are too few education courses which teach high-performance computing from basic to advanced levels. In this study, we derive the knowledge units needed to learn high-performance computing, an important research tool in computational science. Using ACM the Computer Science Curricula 2013 (CS2013), we examine the validity and reliability of 89 knowledge units and eleven knowledge units with high validity and reliability, after which nine core knowledge units and two optional knowledge units are proposed. The eleven proposed knowledge units are expected to contribute to the development of the high-performance computing curriculum necessary to teach computational science.

국내에서는 계산과학이라는 학문이 초기단계로 아직 활성화되지 못하고 있으며 고성능컴퓨팅을 기초부터 고급 과정까지 체계적으로 배울 수 있는 교육체계가 미비하다. 본 논문에서는 계산과학 전공자들이 배워야 할 컴퓨터과학에 대한 기본 연구로 고성능컴퓨팅을 배우기 위해 필요한 지식 단위을 도출하였다. ACM의 Computer Science 커리큘럼(CS2013)을 기초로 하여 89개의 지식 단위들에 대해 타당성과 신뢰성을 조사하였으며 검증된 11개의 지식단위에 대해 전문가를 통해 6개의 핵심 지식 단위와 2개의 선택 지식 단위를 제안되었다. 제안된 지식단위들은 계산과학 전공들에게 필요한 고성능컴퓨팅 교육과정 개발에 기여할 것으로 기대된다.

Keywords

References

  1. U. Rude, K. Willcox, ... & M. Gunzburger, Research and education in computational science and engineering, Siam Review, 2016.
  2. D. E. Stevenson, (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, 1993,
  3. R. E. Tuzun and R. A. McCoy and O. Yasar and K. S. Rajasethupathy and J. Harkin, "A new perspective on computational science education", Computing in Science & Engineering, pp. 74-79, 2000.
  4. O. Yasar and R. H. Landau, Elements of computational science and engineering education, SIAM review, 45(4), 787-805. 2003. https://doi.org/10.1137/S0036144502408075
  5. D. Atkins, T. Hey, and M. Hedstrom. National Science Foundation Advisory Committee for Cyberinfrastructure Task Force on Data and Visualization Final Report. National Science Foundation, 2011.
  6. P. Turner, L. Petzold, A. Shiflet, I. Vakalis, , K. Jordan, & S. S. John, "Undergraduate computational science and engineering education", SIAM review, Vol. 53, No. 3, pp. 561-574, 2011 https://doi.org/10.1137/07070406X
  7. L. Wilson, S. C. John, "Computational science education focused on future domain scientists", Proceedings of the Workshop on Education for High Performance Computing, pp.19-24, IEEE Press. 2016.
  8. C. Tadonki, "Basic parallel and distributed computing curriculum", In Second NSF/TCPP Workshop on Parallel and Distributed Computing Education, The 26th IEEE International Parallel & Distributed Processing Symposium, 2012.
  9. ACM/IEEE-CS Joint Task Force on Computing Curricula, Computer Science Curricula 2013, ACM Press and IEEE Computer Society Press, December 2013
  10. J. Kepner, "HPC productivity: An overarching view", The International Journal of High Performance Computing Applications, Vol. 18, No. 4, pp. 393-397, 2004. https://doi.org/10.1177/1094342004048533
  11. S. L Harrell, H. A. Nam, V. G. V. Larrea, K. Keville, D. Kamalic, "Student cluster competition: a multi-disciplinary undergraduate HPC educational tool", Proceedings of the Workshop on Education for High-Performance Computing, pp. 1-8, November 15, 2015.
  12. M. Richards, S. Lathrop, "A training roadmap for new HPC users", Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, ACM, pp.56, 2011.
  13. M. RSancho, "BSC best practices in professional training and teaching for the HPC ecosystem". Journal of Computational Science, Vol. 14, pp. 74-77, 2016. https://doi.org/10.1016/j.jocs.2015.12.004
  14. D. Akin, M. Belgin, T. A. Bouvet, N. C. Bright, S. Harrell, B. Haymore, & A. Maji, "Linux Clusters Institute Workshops: Building the HPC and Research Computing Systems Professionals Workforce", Proceedings of the HPC Systems Professionals Workshop, ACM. November 2017.
  15. R. J Fehring, "Methods to validate nursing diagnoses", Nursing Faculty Research and Publications, 1987.