KSPComputeEigenvaluesExplicitly#

Computes all of the eigenvalues of the preconditioned operator using LAPACK.

Synopsis#

Collective

Input Parameters#

  • ksp - iterative context obtained from KSPCreate()

  • n - size of arrays r and c

Output Parameters#

  • r - real part of computed eigenvalues, provided by user with a dimension at least of n

  • c - complex part of computed eigenvalues, provided by user with a dimension at least of n

Notes#

This approach is very slow but will generally provide accurate eigenvalue estimates. This routine explicitly forms a dense matrix representing the preconditioned operator, and thus will run only for relatively small problems, say n < 500.

Many users may just want to use the monitoring routine KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value) to print the singular values at each iteration of the linear solve.

The preconditioner operator, rhs vector, solution vectors should be set before this routine is called. i.e use KSPSetOperators(), KSPSolve()

See Also#

KSP: Linear System Solvers, KSP, KSPComputeEigenvalues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues(), KSPSetOperators(), KSPSolve()

Level#

advanced

Location#

src/ksp/ksp/interface/eige.c


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