NAG CL Interface
f12fcc (real_symm_proc)
Note: this function uses optional parameters to define choices in the problem specification. If you wish to use default
settings for all of the optional parameters, then the option setting function f12fdc need not be called.
If, however, you wish to reset some or all of the settings please refer to Section 11 in f12fdc for a detailed description of the specification of the optional parameters.
1
Purpose
f12fcc is a post-processing function in a suite of functions which includes
f12fac,
f12fbc,
f12fdc and
f12fec.
f12fcc must be called following a final exit from
f12fbc.
2
Specification
The function may be called by the names: f12fcc, nag_sparseig_real_symm_proc or nag_real_symm_sparse_eigensystem_sol.
3
Description
The suite of functions is designed to calculate some of the eigenvalues, , (and optionally the corresponding eigenvectors, ) of a standard eigenvalue problem , or of a generalized eigenvalue problem of order , where is large and the coefficient matrices and are sparse, real and symmetric. The suite can also be used to find selected eigenvalues/eigenvectors of smaller scale dense, real and symmetric problems.
Following a call to
f12fbc,
f12fcc returns the converged approximations to eigenvalues and (optionally) the corresponding approximate eigenvectors and/or an orthonormal basis for the associated approximate invariant subspace. The eigenvalues (and eigenvectors) are selected from those of a standard or generalized eigenvalue problem defined by real symmetric matrices. There is negligible additional cost to obtain eigenvectors; an orthonormal basis is always computed, but there is an additional storage cost if both are requested.
f12fcc is based on the function
dseupd from the ARPACK package, which uses the Implicitly Restarted Lanczos iteration method. The method is described in
Lehoucq and Sorensen (1996) and
Lehoucq (2001) while its use within the ARPACK software is described in great detail in
Lehoucq et al. (1998). An evaluation of software for computing eigenvalues of sparse symmetric matrices is provided in
Lehoucq and Scott (1996). This suite of functions offers the same functionality as the ARPACK software for real symmetric problems, but the interface design is quite different in order to make the option setting clearer and to simplify some of the interfaces.
f12fcc, is a post-processing function that must be called following a successful final exit from
f12fbc.
f12fcc uses data returned from
f12fbc and options, set either by default or explicitly by calling
f12fdc, to return the converged approximations to selected eigenvalues and (optionally):
-
–the corresponding approximate eigenvectors;
-
–an orthonormal basis for the associated approximate invariant subspace;
-
–both.
4
References
Lehoucq R B (2001) Implicitly restarted Arnoldi methods and subspace iteration SIAM Journal on Matrix Analysis and Applications 23 551–562
Lehoucq R B and Scott J A (1996) An evaluation of software for computing eigenvalues of sparse nonsymmetric matrices Preprint MCS-P547-1195 Argonne National Laboratory
Lehoucq R B and Sorensen D C (1996) Deflation techniques for an implicitly restarted Arnoldi iteration SIAM Journal on Matrix Analysis and Applications 17 789–821
Lehoucq R B, Sorensen D C and Yang C (1998) ARPACK Users' Guide: Solution of Large-scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods SIAM, Philadelphia
5
Arguments
-
1:
– Integer *
Output
-
On exit: the number of converged eigenvalues as found by
f12fbc.
-
2:
– double
Output
-
Note: the dimension,
dim, of the array
d
must be at least
(see
f12fac).
On exit: the first
nconv locations of the array
d contain the converged approximate eigenvalues.
-
3:
– double
Output
-
On exit: if the default option
(see
f12fdc) has been selected then
z contains the final set of eigenvectors corresponding to the eigenvalues held in
d. The real eigenvector associated with an eigenvalue is stored in the corresponding array section of
z.
-
4:
– double
Input
-
On entry: if one of the
(see
f12fdc) modes has been selected then
sigma contains the real shift used; otherwise
sigma is not referenced.
-
5:
– const double
Input
-
Note: the dimension,
dim, of the array
resid
must be at least
(see
f12fac).
On entry: must not be modified following a call to
f12fbc since it contains data required by
f12fcc.
-
6:
– double
Input/Output
-
The th element of the th basis vector is stored in location , for and .
On entry: the
ncv sections of
v, of length
, contain the Lanczos basis vectors for
as constructed by
f12fbc.
On exit: if the option
has been set, or the option
has been set and a separate array
z has been passed (i.e.,
z does not equal
v), then the first
nconv sections of
v, of length
, will contain approximate Schur vectors that span the desired invariant subspace.
-
7:
– double
Communication Array
-
Note: the actual argument supplied
must be the array
comm supplied to the initialization routine
f12fac.
On initial entry: must remain unchanged from the prior call to
f12fac.
On exit: contains data on the current state of the solution.
-
8:
– Integer
Communication Array
-
Note: the actual argument supplied
must be the array
icomm supplied to the initialization routine
f12fac.
On initial entry: must remain unchanged from the prior call to
f12fac.
On exit: contains data on the current state of the solution.
-
9:
– NagError *
Input/Output
-
The NAG error argument (see
Section 7 in the Introduction to the NAG Library CL Interface).
6
Error Indicators and Warnings
- NE_ALLOC_FAIL
-
Dynamic memory allocation failed.
See
Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
- NE_BAD_PARAM
-
On entry, argument had an illegal value.
- NE_INTERNAL_ERROR
-
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact
NAG for assistance.
See
Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
- NE_INVALID_OPTION
-
On entry, , but this is not yet implemented.
- NE_MAX_ITER
-
During calculation of a tridiagonal form, there was a failure to compute eigenvalues in a total of iterations.
- NE_MISSING_CALL
-
Either the function was called out of sequence (following an initial call to the setup function and following completion of calls to the reverse communication function) or the communication arrays have become corrupted.
- NE_NO_LICENCE
-
Your licence key may have expired or may not have been installed correctly.
See
Section 8 in the Introduction to the NAG Library CL Interface for further information.
- NE_RITZ_COUNT
-
Got a different count of the number of converged Ritz values than the value passed to it through the argument
icomm: number counted
, number expected
. This usually indicates that a communication array has been altered or has become corrupted between calls to
f12fbc and
f12fcc.
- NE_ZERO_EIGS_FOUND
-
The number of eigenvalues found to sufficient accuracy, as communicated through the argument
icomm, is zero. You should experiment with different values of
nev and
ncv, or select a different computational mode or increase the maximum number of iterations prior to calling
f12fbc.
7
Accuracy
The relative accuracy of a Ritz value,
, is considered acceptable if its Ritz estimate
. The default
used is the
machine precision given by
X02AJC.
8
Parallelism and Performance
Background information to multithreading can be found in the
Multithreading documentation.
f12fcc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f12fcc makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the
X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the
Users' Note for your implementation for any additional implementation-specific information.
None.
10
Example
This example solves in regular mode, where and are obtained from the standard central difference discretization of the one-dimensional Laplacian operator
on , with zero Dirichlet boundary conditions.
10.1
Program Text
10.2
Program Data
10.3
Program Results