This course will provide an interdisciplinary, project-oriented, experience in the computational solution of large-scale problems in science and engineering. The course may be taken at either the 400 or 600 levels. Graduate students will typically serve as team leaders for computational projects that address realistic scientific or engineering applications.

Interdisciplinary project teams will be formed to include computer scientists, mathematicians, and natural scientists or engineers. Instructors will provide information on core computational techniques, computer architectures, and applications. Material will include parallel computation, visualization, data representation, and finite difference and finite element applications.

The interdisciplinary experience will simulate an industrial development environment; hence, prerequisites have been kept minimal. Undergraduates should have a mathematical knowledge through elementary differential equations and some programming experience. Science and engineering students in their second junior semester should be able to take the course. Computer Science and Computer Engineering majors might take it a semester earlier. Graduate students should have some knowledge of numerical computing obtained from, e.g., a finite element or a numerical analysis course.