The Interdisciplinary Program of Computational Science and Technology (IPCST) was established in order to encourage interdisciplinary researches on theory, technology and practical applications of scientific advanced computational science, such as parallel supercomputing, and it is further supposed to foster progress of scientific computing fields and obtain high-quality human resources by educating outstanding students for master or doctoral degree, who can effectively apply to and develop application areas such as natural science, engineering, and medicine.



With theory and experiment, two frameworks for advances of scientific knowledge and engineering applications in science, engineering, medicine, and industry, both scientific calculation and simulation have already become indispensable and important. Numerical simulation is a nearly unique, efficient, and powerful alternative to study complex systems and natural phenomena, for which performing a direct experiment is too costly, dangerous, or even impossible. On the other hand, most of the challenges of numerical simulations of natural and applied sciences, which had not been challenged in the past due to large memory and long calculation time, are now treated as problems that can be computed in short time, maintaining the detail and realism of a higher level with a cheaper parallel supercomputer thanks to rapid progress of parallel supercomputing over the past decade.

Therefore, many computational problems, which have been studied separately in natural science and in applied science, can be dealt with in a new paradigm, parallel supercomputing. Traditionally long, computation has been used as a tool to validate fundamental principles or logics in science, especially math fields. By utilizing powerful computers, however, the position and importance of computation used in scientific exploration and its applications have greatly changed. The continued evolution of computer technology has served as a driving force for advancement of modern IT (Information Technology), and computational power has also made remarkable improvements. Consequently, research and technological innovation that were impossible come true. Computation now becomes one of three fundamental axes of scientific exploration, with theory and experiment, and opens new possibilities to every discipline, not only science, to bring new paradigm to scientific research.

In fact, new tool computers are putting spotlights to different aspects of science theories, and simulation by various methods is developing new field of science combining theory and experiment. Without computers, BT(Bio-technology) and NT(Nano-technology) are impossible. This type of science development, however, cannot be achieved by using computers simply or bringing traditional computer engineering methods. Although computers are good and essential tools for scientific research of scientists and engineers, the ultimate interest and objective of scientists and engineers are advancement of science and practical application themselves.

This requires a new form of study combining science and mathematics, and advanced countries recognized this importance to foster these kinds of researches and educations systematically in the name of ‘Computational Science & Engineering’ (References: Links 1 & 2). Such investments have been concentrated in this area by labs in the US since the 50’s and 60's. For example, Argonne National Lab (DOE Mathematical, Information, and Computational Science Division), Lawrence Livermore National Lab (Applied Simulation and Computation), Los Alamos National Lab (The Computing and Communications Division) have strategically developed people for the scientific, military, and commercial purposes of scientific computation, and the United States has been able to uphold the leading position of scientific technology thanks to it.



Although computational science, requiring high-end scientific computing such as parallel supercomputing, manifests diverse features in diverse practical applications, its common elements are based on fundamental knowledge of mathematical methodologies such as numerical analysis, computational algorithms, and statistical processing, and it requires new calculation methods (high-speed high-throughput computation, simulation, modeling, visualization, and data analysis) and combination of individual science and engineering, which feature comprehensive and interdisciplinary character. However, in the current situation where fields of computational science are split, it is improbable andunaffordable to recruit or to cultivate new people voluntarily by each field.

As synergy cannot be feasible to scattered fields in various departments or majors, now is the point whenpeople cannot overlook the importance of highly advanced computing techniques, such as parallel supercomputing, which is rapidly progressing in advanced countries. Particularly, ‘Computational Science & Engineering’ requiring parallel supercomputing is not only an integral part of development of future industries as a fusion discipline combining natural sciences and applied sciences like engineering, but also needs to be established as a reliable discipline. Leading foreign universities have already begun interdisciplinary programs of computational science to adapt themselves to these changes and are trying to form a critical mass. Such a global trend provides us with the justification for developing reference science. Many overseas universities are already running computational science education programs. In addition to the reference 1 which shows a part of the computational science program list of some universities collected by SIAM (Society of Industrial and Applied Mathematics), many universities in advanced countries, competitively, have various forms of interdisciplinary computational science programs to try to take the lead.

Thus, we should establish a program to systematically and efficiently explore and transfer computational science in graduate schools, thereby creating a program to educate a curriculum reconciling computer knowledge prerequisite for advanced computational science with each science and its applications. Another reason is to provide opportunities of connecting advanced computational science knowledge and infrastructure created in an independent area of SNU with the other research areas, encouraging more vigorous communication among areas which need advanced computational science. Furthermore, it is necessary to reduce redundant computational science subjects in several departments and colleges for maximum efficiency of relevant course lectures in SNU.