CSE548
This course concerns scientific computation in a broad sense. We will use numerical libraries written in higher level languages, such as C, Fortran, and Python, to solve computational problems. Emphasis will be placed on computational decision making. For example, how should I choose which nonlinear solver to use? How should I evaluate its suitability once I have tried it? We will also cover basic techniques of algorithm design and implementation, project planning, source management, configuration and build tools, documentation, program construction, i/o, and visualization.
If you go on to career in scientific computing, you will very often be confronted with models, discretizations, numerical methods, and solution algorithms unfamiliar to you. Some you will research and understand completely, and some you will understand at a merely mechanical level. This course mirrors that experience. When you first did arthmetic, were you aware you were doing it in an algebraically closed field or why?