Numerical Linear Algebra for Computational Science and Information Engineering (CITHN2006)

Home, Research, Teaching, Software

The course is organized into lectures selected from the following list of topics:

Essentials of linear algebra [slides]

Introduction to the Julia language [slides]

Floating-point arithmetic and error analysis [slides]

Direct methods for dense linear systems [slides]

Sparse data structures and basic linear algebra subprograms [slides]

Introduction to direct methods for sparse linear systems [slides]

Orthogonalization and least-squares problems [slides]

Basic iterative methods for linear systems [slides]

Basic iterative methods for eigenvalue problems [slides]

Locally optimal block preconditioned conjugate gradient [slides]

Arnoldi and Lanczos procedures [slides]

Jacobi-Davidson methods [slides, notebook]

Krylov subspace methods for linear systems [slides]

Preconditioned iterative methods for linear systems [slides]

Final exams: Summer 2025 [pdf]