Numerical Linear Algebra for Computational Science and Information Engineering (CITHN2006)
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The course is organized into lectures selected from the following list of topics:
Essentials of linear algebra [pdf]
Floating-point arithmetic and error analysis [pdf]
Direct methods for dense linear systems [pdf]
Sparse data structures and basic linear algebra subprograms [pdf]
Introduction to direct methods for sparse linear systems [pdf]
Orthogonalization and least-squares problems [pdf]
Basic iterative methods for linear systems [pdf]
Basic iterative methods for eigenvalue problems [pdf]
Locally optimal block preconditioned conjugate gradient [pdf]
Arnoldi and Lanczos procedures [pdf]
Jacobi-Davidson methods [pdf]
Krylov subspace methods for linear systems [pdf]
Preconditioned iterative methods for linear systems [pdf]
Restarted Krylov subspace methods [pdf]
Introduction to communication-avoiding algorithms [pdf]
Final exams: Summer 2025 [pdf]