Numerical Methods for High Performance Computing
Period: Second semester
Course unit contents:
1. Advanced numerical linear algebra: projection methods for non-symmetric systems (Bi-CG, QMR) and eigenproblems (Power Method, QR Method, Lanczos, DACG);
2. Multigrid;
3. Preconditioning techniques: ILU, approximate inverses, AMG;
4. Parallel numerical analysis: basic concepts, operations and communications, data structures;
5. Parallel programming paradigms: OpenMP and Message Passing Interface standards;
6. Parallel implementations: sparse linear algebra kernels, iterative methods, domain decomposition.
Planned learning activities and teaching methods:
In addition to contacting the course instructor, students with disabilities, Specific Learning Disorders (SLD), Special Educational Needs (SEN), and other health conditions can reach out to the Student Services Office - Inclusion Unit to receive more information about opportunities to access teaching with specific support and tools