MTAT.08.010 Teadusarvutused / Scientific Computing
Lectures: Monday 18:15-20:00 Liivi 2-206 (Tentative)
Computer Classes: Wednesday 16:15-18:00 Liivi 2-205 (Tentative)
Objectives
During the course, students obtain practical experience on problems and solution processes in scientific computing. Students develop an ability to solve new scientific problems efficiently. Students obtain insight on benefits and problems from parallelization of large computations.
Learning outcomes
Course participants obtain knowledge of recent scientific computing problems, their solution methodologies, software implementations, programming languages; can design their solution algorithms, program these and use scientific computing libraries.
Brief description
- What is scientific computing?
- Typical problems in scientific computation
floating-point arithmetic
large problems in linear algebra
condition number
complexity analysis of algorithms, closer coverage as an example - Gaussian Elimination method,
memory hierarchies in modern processors
numerical libraries BLAS and LAPACK
- Scientific visualization
- Applications:
numerical integration and differentiation
numerical solution of integral and differential equations
application of parallel computers in large computations
- Parallel program performance
- Domain Decomposition for solution of partial differential equations