arnoldi_api Module Reference

arnoldi iteration using dbcsr More...

Functions/Subroutines
subroutine, public	arnoldi_ev (matrix, arnoldi_data)
	Driver routine for different arnoldi eigenvalue methods the selection which one is to be taken is made beforehand in the setup call passing the generalized_ev flag or not. More...
subroutine, public	arnoldi_extremal (matrix_a, max_ev, min_ev, converged, threshold, max_iter)
	simple wrapper to estimate extremal eigenvalues with arnoldi, using the old lanczos interface this hides some of the power of the arnoldi routines (e.g. only min or max eval, generalized eval, ritz vectors, etc.), and does not allow for providing an initial guess of the ritz vector. More...
subroutine, public	arnoldi_conjugate_gradient (matrix_a, vec_x, matrix_p, converged, threshold, max_iter)
	Wrapper for conjugated gradient algorithm for Ax=b. More...

Detailed Description

arnoldi iteration using dbcsr

History

2014.09 created [Florian Schiffmann]

Author

Florian Schiffmann

Function/Subroutine Documentation

arnoldi_ev()

subroutine, public arnoldi_api::arnoldi_ev	(	type(dbcsr_p_type), dimension(:)	matrix,
		type(arnoldi_data_type)	arnoldi_data
	)

Driver routine for different arnoldi eigenvalue methods the selection which one is to be taken is made beforehand in the setup call passing the generalized_ev flag or not.

Parameters

matrix	...
arnoldi_data	...

Definition at line 68 of file arnoldi_api.F.

Here is the call graph for this function:

Here is the caller graph for this function:

arnoldi_extremal()

subroutine, public arnoldi_api::arnoldi_extremal	(	type(dbcsr_type), intent(inout), target	matrix_a,
		real(kind=dp), intent(out)	max_ev,
		real(kind=dp), intent(out)	min_ev,
		logical, intent(out)	converged,
		real(kind=dp), intent(in)	threshold,
		integer, intent(in)	max_iter
	)

simple wrapper to estimate extremal eigenvalues with arnoldi, using the old lanczos interface this hides some of the power of the arnoldi routines (e.g. only min or max eval, generalized eval, ritz vectors, etc.), and does not allow for providing an initial guess of the ritz vector.

Parameters

matrix_a	input mat
max_ev	estimated max eval
min_ev	estimated min eval
converged	Usually arnoldi is more accurate than claimed.
threshold	target precision
max_iter	max allowed iterations (will be rounded up)

Definition at line 253 of file arnoldi_api.F.

Here is the call graph for this function:

Here is the caller graph for this function:

arnoldi_conjugate_gradient()

subroutine, public arnoldi_api::arnoldi_conjugate_gradient	(	type(dbcsr_type), intent(in), target	matrix_a,
		real(kind=dp), dimension(:), intent(inout)	vec_x,
		type(dbcsr_type), intent(in), optional, target	matrix_p,
		logical, intent(out)	converged,
		real(kind=dp), intent(in)	threshold,
		integer, intent(in)	max_iter
	)

Wrapper for conjugated gradient algorithm for Ax=b.

Parameters

matrix_a	input mat
vec_x	input right hand side vector; output solution vector, fully replicated!
matrix_p	input preconditioner (optional)
converged	...
threshold	target precision
max_iter	max allowed iterations

Definition at line 302 of file arnoldi_api.F.

Here is the call graph for this function:

Here is the caller graph for this function: