Iterative Solvers

Iterative solvers approximate the solution through repeated updates. They are often more memory efficient than direct solvers and can be effective for very large sparse systems.

Solver performance depends strongly on matrix conditioning and preconditioning. Convergence tolerances should be chosen to balance accuracy and computational cost.