Purpose
To solve the system of linear equations Ax = b, with A symmetric, positive definite, or, in the implicit form, f(A, x) = b, where y = f(A, x) is a symmetric positive definite linear mapping from x to y, using the conjugate gradient (CG) algorithm without preconditioning.Specification
SUBROUTINE MB02WD( FORM, F, N, IPAR, LIPAR, DPAR, LDPAR, ITMAX,
$ A, LDA, B, INCB, X, INCX, TOL, DWORK, LDWORK,
$ IWARN, INFO )
C .. Scalar Arguments ..
CHARACTER FORM
INTEGER INCB, INCX, INFO, ITMAX, IWARN, LDA, LDPAR,
$ LDWORK, LIPAR, N
DOUBLE PRECISION TOL
C .. Array Arguments ..
DOUBLE PRECISION A(LDA,*), B(*), DPAR(*), DWORK(*), X(*)
INTEGER IPAR(*)
Arguments
Mode Parameters
FORM CHARACTER*1
Specifies the form of the system of equations, as
follows:
= 'U' : Ax = b, the upper triagular part of A is used;
= 'L' : Ax = b, the lower triagular part of A is used;
= 'F' : the implicit, function form, f(A, x) = b.
Function Parameters
F EXTERNAL
If FORM = 'F', then F is a subroutine which calculates the
value of f(A, x), for given A and x.
If FORM <> 'F', then F is not called.
F must have the following interface:
SUBROUTINE F( N, IPAR, LIPAR, DPAR, LDPAR, A, LDA, X,
$ INCX, DWORK, LDWORK, INFO )
where
N (input) INTEGER
The dimension of the vector x. N >= 0.
IPAR (input) INTEGER array, dimension (LIPAR)
The integer parameters describing the structure of
the matrix A.
LIPAR (input) INTEGER
The length of the array IPAR. LIPAR >= 0.
DPAR (input) DOUBLE PRECISION array, dimension (LDPAR)
The real parameters needed for solving the
problem.
LDPAR (input) INTEGER
The length of the array DPAR. LDPAR >= 0.
A (input) DOUBLE PRECISION array, dimension
(LDA, NC), where NC is the number of columns.
The leading NR-by-NC part of this array must
contain the (compressed) representation of the
matrix A, where NR is the number of rows of A
(function of IPAR entries).
LDA (input) INTEGER
The leading dimension of the array A.
LDA >= MAX(1,NR).
X (input/output) DOUBLE PRECISION array, dimension
(1+(N-1)*INCX)
On entry, this incremented array must contain the
vector x.
On exit, this incremented array contains the value
of the function f, y = f(A, x).
INCX (input) INTEGER
The increment for the elements of X. INCX > 0.
DWORK DOUBLE PRECISION array, dimension (LDWORK)
The workspace array for subroutine F.
LDWORK (input) INTEGER
The size of the array DWORK (as large as needed
in the subroutine F).
INFO INTEGER
Error indicator, set to a negative value if an
input scalar argument is erroneous, and to
positive values for other possible errors in the
subroutine F. The LAPACK Library routine XERBLA
should be used in conjunction with negative INFO.
INFO must be zero if the subroutine finished
successfully.
Parameters marked with "(input)" must not be changed.
Input/Output Parameters
N (input) INTEGER
The dimension of the vector x. N >= 0.
If FORM = 'U' or FORM = 'L', N is also the number of rows
and columns of the matrix A.
IPAR (input) INTEGER array, dimension (LIPAR)
If FORM = 'F', the integer parameters describing the
structure of the matrix A.
This parameter is ignored if FORM = 'U' or FORM = 'L'.
LIPAR (input) INTEGER
The length of the array IPAR. LIPAR >= 0.
DPAR (input) DOUBLE PRECISION array, dimension (LDPAR)
If FORM = 'F', the real parameters needed for solving
the problem.
This parameter is ignored if FORM = 'U' or FORM = 'L'.
LDPAR (input) INTEGER
The length of the array DPAR. LDPAR >= 0.
ITMAX (input) INTEGER
The maximal number of iterations to do. ITMAX >= 0.
A (input) DOUBLE PRECISION array,
dimension (LDA, NC), if FORM = 'F',
dimension (LDA, N), otherwise.
If FORM = 'F', the leading NR-by-NC part of this array
must contain the (compressed) representation of the
matrix A, where NR and NC are the number of rows and
columns, respectively, of the matrix A. The array A is
not referenced by this routine itself, except in the
calls to the routine F.
If FORM <> 'F', the leading N-by-N part of this array
must contain the matrix A, assumed to be symmetric;
only the triangular part specified by FORM is referenced.
LDA (input) INTEGER
The leading dimension of array A.
LDA >= MAX(1,NR), if FORM = 'F';
LDA >= MAX(1,N), if FORM = 'U' or FORM = 'L'.
B (input) DOUBLE PRECISION array, dimension (1+(N-1)*INCB)
The incremented vector b.
INCB (input) INTEGER
The increment for the elements of B. INCB > 0.
X (input/output) DOUBLE PRECISION array, dimension
(1+(N-1)*INCX)
On entry, this incremented array must contain an initial
approximation of the solution. If an approximation is not
known, setting all elements of x to zero is recommended.
On exit, this incremented array contains the computed
solution x of the system of linear equations.
INCX (input) INTEGER
The increment for the elements of X. INCX > 0.
Tolerances
TOL DOUBLE PRECISION
If TOL > 0, absolute tolerance for the iterative process.
The algorithm will stop if || Ax - b ||_2 <= TOL. Since
it is advisable to use a relative tolerance, say TOLER,
TOL should be chosen as TOLER*|| b ||_2.
If TOL <= 0, a default relative tolerance,
TOLDEF = N*EPS*|| b ||_2, is used, where EPS is the
machine precision (see LAPACK Library routine DLAMCH).
Workspace
DWORK DOUBLE PRECISION array, dimension (LDWORK)
On exit, if INFO = 0, DWORK(1) returns the number of
iterations performed and DWORK(2) returns the remaining
residual, || Ax - b ||_2.
LDWORK INTEGER
The length of the array DWORK.
LDWORK >= MAX(2,3*N + DWORK(F)), if FORM = 'F',
where DWORK(F) is the workspace needed by F;
LDWORK >= MAX(2,3*N), if FORM = 'U' or FORM = 'L'.
Warning Indicator
IWARN INTEGER
= 0: no warning;
= 1: the algorithm finished after ITMAX > 0 iterations,
without achieving the desired precision TOL;
= 2: ITMAX is zero; in this case, DWORK(2) is not set.
Error Indicator
INFO INTEGER
= 0: successful exit;
< 0: if INFO = -i, the i-th argument had an illegal
value;
> 0: if INFO = i, then F returned with INFO = i.
Method
The following CG iteration is used for solving Ax = b:
Start: q(0) = r(0) = Ax - b
< q(k), r(k) >
ALPHA(k) = - ----------------
< q(k), Aq(k) >
x(k+1) = x(k) - ALPHA(k) * q(k)
r(k+1) = r(k) - ALPHA(k) * Aq(k)
< r(k+1), r(k+1) >
BETA(k) = --------------------
< r(k) , r(k) >
q(k+1) = r(k+1) + BETA(k) * q(k)
where <.,.> denotes the scalar product.
References
[1] Golub, G.H. and van Loan, C.F.
Matrix Computations. Third Edition.
M. D. Johns Hopkins University Press, Baltimore, pp. 520-528,
1996.
[2] Luenberger, G.
Introduction to Linear and Nonlinear Programming.
Addison-Wesley, Reading, MA, p.187, York, 1973.
Numerical Aspects
Since the residuals are orthogonal in the scalar product
<x, y> = y'Ax, the algorithm is theoretically finite. But rounding
errors cause a loss of orthogonality, so a finite termination
cannot be guaranteed. However, one can prove [2] that
|| x-x_k ||_A := sqrt( (x-x_k)' * A * (x-x_k) )
sqrt( kappa_2(A) ) - 1
<= 2 || x-x_0 ||_A * ------------------------ ,
sqrt( kappa_2(A) ) + 1
where kappa_2 is the condition number.
The approximate number of floating point operations is
(k*(N**2 + 15*N) + N**2 + 3*N)/2, if FORM <> 'F',
k*(f + 7*N) + f, if FORM = 'F',
where k is the number of CG iterations performed, and f is the
number of floating point operations required by the subroutine F.
Further Comments
NoneExample
Program Text
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NoneProgram Results
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