Unstructured sparse matrices and vectors with iterative solvers and preconditioners. The classes and interfaces can be grouped as follows:

- General sparse matrices
  - CompRowMatrix - Compressed row storage. Generally the best sparse matrix if the non-zero structure is known.
  - CompColMatrix - Compressed column storage.
  - CompDiagMatrix - Compressed diagonal storage.
  - FlexCompRowMatrix - Flexible compressed row storage. Stores each row as a growable sparse vector.
  - FlexCompColMatrix - Flexible compressed column storage. Stores each column as a growable sparse vector.
  - SparseVector - Growable sparse vector.
- Iterative solvers
  - BiCG - BiConjugate gradients.
  - BiCGstab - BiConjugate gradients stabilized.
  - CG - Conjugate gradients.
  - CGS - Conjugate gradients squared.
  - Chebyshev - The Chebyshev iteration for symmetrical, positive definite matrices.
  - GMRES - Generalized minimal residual using restart.
  - IR - Iterative refinement (Richardson's method).
  - QMR - Quasi-minimal residual.
- Preconditioners
  - DiagonalPreconditioner - Diagonal preconditioning.
  - SSOR - Symmetrical sucessive overrelaxation.
  - ICC - Incomplete Cholesky without fill-in.
  - ILU - Incomplete LU without fill-in.
  - ILUT - Incomplete LU with fill-in using a threshold approach.
  - AMG - Algebraic multigrid by smoothed aggregation.