Explores iterative methods for solving linear systems, including Jacobi and Gauss-Seidel methods, Cholesky factorization, and preconditioned conjugate gradient.
Covers the Conjugate Gradient method for solving linear systems without pre-conditioning, exploring parallel computing implementations and performance predictions.
