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Parallel Matrix Computations

Class at Faculty of Mathematics and Physics |
NMNV532

Syllabus

1. Computational models for parallel architectures.

2. Basic parallel operations with dense and sparse matrices.

3. Preconditioning and preconditioned Krylov space methods.

4. Domain decomposition and multigrid methods.

5. Parallelization of direct methods for sparse matrices.

Annotation

The goal of this course is to introduce parallel processing of basic computational cores that can be encountered in mathematical modeling as well as in scientific computing in general. These cores include, for example, basic operations with dense and sparse matrices and preconditioning of

Krylov space methods. The course includes also elementary introduction into multigrid and domain decomposition methods.