Previous: Summary of Choices.
For each algorithm we have
distinguished between different ways of running the algorithm:
- is direct application, where we multiply with and solve with .
- is shift and invert, which solves systems
and multiplies with . This gives
the ability to compute a wider choice of eigenvalues in fewer iterations.
- means application with a preconditioner, for instance,
a sparse approximate factorization. This needs
less space than shift and invert, but most often it also needs a larger number of matrix-vector multiplies.