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 SCOPES Project 7 IP 65642  

What is CSE




Computation is now regarded as an equal and indispensable partner, along with theory and experiment, in the advance of scientific knowledge and engineering practice. Numerical simulation enables the study of complex systems and natural phenomena that would be too expensive or dangerous, or even impossible, to study by direct experimentation. The quest for ever higher levels of detail and realism in such simulations requires enormous computational capacity, and has provided the impetus for dramatic breakthroughs in computer algorithms and architectures. Due to these advances, computational scientists and engineers can now solve large-scale problems that were
once thought intractable.

Computational Science and Engineering (CSE) is a broad multidisciplinary area that encompasses applications in science/engineering, applied mathematics, numerical analysis, and computer science. Computer models and computer simulations have become an important part of the research repertoire, supplementing (and in some cases replacing) experimentation. Going from application area to computational results requires domain expertise, mathematical modeling, numerical analysis, algorithm development, software implementation, program execution, analysis, validation and visualization of results. CSE involves all of this.

CSE is a legitimate and important academic enterprise, even if it has yet to be formally recognized as such at some institutions. Although it includes elements from computer science, applied mathematics, engineering and science, CSE focuses on the integration of knowledge and methodologies from all of these disciplines, and as such is a subject which is distinct from any of them.

CSE makes use of the techniques of applied mathematics and computer science for the development of problem-solving methodologies and robust tools which will be the building blocks for solutions to scientific and engineering problems of ever- increasing complexity. It differs from mathematics or computer science in that analysis and methodologies are directed specifically at the solution of problem classes from science and engineering, and will generally require a detailed knowledge or substantial collaboration from those disciplines. The computing and mathematical techniques used may be more domain specific, and the computer science and mathematics skills needed will be broader.

CSE as an Emerging Discipline. Although some researchers have been doing what might now be called CSE research for quite some time, for a number of reasons we appear to be at a critical juncture in terms of the role being played by simulation in science and industry. Historically, simulation has been used as a qualitative guide for design and control, but has often not been expected to provide accurate results for realistic physical systems. Increasingly, simulation is being used in a more quantitative way, as an integral part of the manufacturing, design and decision-making processes, and as a fundamental tool for scientific research. Problems where CSE has played and is expected to continue to play a pivotal role include: weather and climate prediction, combustion, simulation, design and control of vehicles, aircraft design, electronic design automation, etc.

CSE tools are critical in the exploration of scientific areas such as astrophysics, quantum mechanics, relativity, chemistry and molecular biology, where experiments are difficult and expensive if not impossible, and in analyzing the reams of experimental data and developing models in emerging areas such as biology, chemistry, material sciences, bioengineering, etc.

Enabling technologies for CSE. Growth in the expectations for and applications of CSE methodology has been fueled by rapid and sustained advances over the past twenty years of computing power and algorithm speed and reliability, and the emergence of software tools for the development and integration of complex software systems and the visualization of results. In many areas of science and engineering, the boundary has been crossed where simulation, or simulation in combination with experiment is more effective (in some combination of time/cost/accuracy) than experiment alone for real needs.


The interdisciplinary character of CSE requires new structures in research and education. Research in CSE cannot be successful without collaboration among members of various disciplines. Establishing an umbrella institution embracing interested departments and research facilities is one of the goals of the proposed activities.

Correspondingly, at universities, a curriculum for the education in Computational Science and Engineering is to be developed.


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