Students will be able to select and apply fundamental methods of scientific computing and to judge the challenges regarding computing time and implementation effort.
Furthermore, the students have solution skills for inter-disciplinary problems, are able to evaluate and analyze computational approaches, and are able to scientifically formulate and extensively analyze compute-intensive problems as well as develop appropriate approaches.
Content:
Computer Architectures
Serial Optimization
Numerical Derivatives and Integrals
Finite Difference Discretization
Numerical Linear Algebra
Random Number Generation and Monte Carlo Methods
Shared Memory Parallel Computing
Algorithmic Complexity and Data Structures
Mesh Generation and Visualization
Software Engineering Principles for Scientific Computing
A network of +20 European and non-European Universities, coordinated by Department of Information Engineering, Computer Science and Mathematics (DISIM) at University of L'Aquila in Italy (UAQ)