• Journal of The Korean Association of Information Education
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• v.22 no.5
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• pp.545-556
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• 2018

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.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.21-31
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• 2018

In order to utilize HPC in Computational science, It is necessary to learn the knowledge and skills of computer science such as programming, algorithms and data structure. In this paper, we investigate IT education status in Computational science and propose policy directions to improve the HPC education through user survey. To do this, we surveyed the current state of IT subjects among major subjects in physics, chemistry, life sciences, and earth science in domestic universities and surveyed the users' Recognition of HPC education. As a result, the ratio of IT subjects in Computational science was very lower than the ratio of major domain subjects. Despite the high educational needs of universities, the educational level of universities was the lowest. Most users have learned the necessary knowledge and skills through self-study. We recognized the role of the university is the most urgent and important, and the role of professional institutions and online education is also important.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.1021-1026
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• 2018

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.