*DECK DCGS
SUBROUTINE DCGS (N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MSOLVE,
+ ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT, R, R0, P, Q, U, V1,
+ V2, RWORK, IWORK)
C***BEGIN PROLOGUE DCGS
C***PURPOSE Preconditioned BiConjugate Gradient Squared Ax=b Solver.
C Routine to solve a Non-Symmetric linear system Ax = b
C using the Preconditioned BiConjugate Gradient Squared
C method.
C***LIBRARY SLATEC (SLAP)
C***CATEGORY D2A4, D2B4
C***TYPE DOUBLE PRECISION (SCGS-S, DCGS-D)
C***KEYWORDS BICONJUGATE GRADIENT, ITERATIVE PRECONDITION,
C NON-SYMMETRIC LINEAR SYSTEM, SLAP, SPARSE
C***AUTHOR Greenbaum, Anne, (Courant Institute)
C Seager, Mark K., (LLNL)
C Lawrence Livermore National Laboratory
C PO BOX 808, L-60
C Livermore, CA 94550 (510) 423-3141
C seager@llnl.gov
C***DESCRIPTION
C
C *Usage:
C INTEGER N, NELT, IA(NELT), JA(NELT), ISYM, ITOL, ITMAX
C INTEGER ITER, IERR, IUNIT, IWORK(USER DEFINED)
C DOUBLE PRECISION B(N), X(N), A(NELT), TOL, ERR, R(N), R0(N), P(N)
C DOUBLE PRECISION Q(N), U(N), V1(N), V2(N), RWORK(USER DEFINED)
C EXTERNAL MATVEC, MSOLVE
C
C CALL DCGS(N, B, X, NELT, IA, JA, A, ISYM, MATVEC,
C $ MSOLVE, ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT,
C $ R, R0, P, Q, U, V1, V2, RWORK, IWORK)
C
C *Arguments:
C N :IN Integer
C Order of the Matrix.
C B :IN Double Precision B(N).
C Right-hand side vector.
C X :INOUT Double Precision X(N).
C On input X is your initial guess for solution vector.
C On output X is the final approximate solution.
C NELT :IN Integer.
C Number of Non-Zeros stored in A.
C IA :IN Integer IA(NELT).
C JA :IN Integer JA(NELT).
C A :IN Double Precision A(NELT).
C These arrays contain the matrix data structure for A.
C It could take any form. See "Description", below,
C for more details.
C ISYM :IN Integer.
C Flag to indicate symmetric storage format.
C If ISYM=0, all non-zero entries of the matrix are stored.
C If ISYM=1, the matrix is symmetric, and only the upper
C or lower triangle of the matrix is stored.
C MATVEC :EXT External.
C Name of a routine which performs the matrix vector multiply
C operation Y = A*X given A and X. The name of the MATVEC
C routine must be declared external in the calling program.
C The calling sequence of MATVEC is:
C CALL MATVEC( N, X, Y, NELT, IA, JA, A, ISYM )
C Where N is the number of unknowns, Y is the product A*X upon
C return, X is an input vector. NELT, IA, JA, A and ISYM
C define the SLAP matrix data structure: see Description,below.
C MSOLVE :EXT External.
C Name of a routine which solves a linear system MZ = R for Z
C given R with the preconditioning matrix M (M is supplied via
C RWORK and IWORK arrays). The name of the MSOLVE routine
C must be declared external in the calling program. The
C calling sequence of MSOLVE is:
C CALL MSOLVE(N, R, Z, NELT, IA, JA, A, ISYM, RWORK, IWORK)
C Where N is the number of unknowns, R is the right-hand side
C vector, and Z is the solution upon return. NELT, IA, JA, A
C and ISYM define the SLAP matrix data structure: see
C Description, below. RWORK is a double precision array that
C can be used to pass necessary preconditioning information and/
C or workspace to MSOLVE. IWORK is an integer work array for
C the same purpose as RWORK.
C ITOL :IN Integer.
C Flag to indicate type of convergence criterion.
C If ITOL=1, iteration stops when the 2-norm of the residual
C divided by the 2-norm of the right-hand side is less than TOL.
C This routine must calculate the residual from R = A*X - B.
C This is unnatural and hence expensive for this type of iter-
C ative method. ITOL=2 is *STRONGLY* recommended.
C If ITOL=2, iteration stops when the 2-norm of M-inv times the
C residual divided by the 2-norm of M-inv times the right hand
C side is less than TOL, where M-inv time a vector is the pre-
C conditioning step. This is the *NATURAL* stopping for this
C iterative method and is *STRONGLY* recommended.
C ITOL=11 is often useful for checking and comparing different
C routines. For this case, the user must supply the "exact"
C solution or a very accurate approximation (one with an error
C much less than TOL) through a common block,
C COMMON /DSLBLK/ SOLN( )
C If ITOL=11, iteration stops when the 2-norm of the difference
C between the iterative approximation and the user-supplied
C solution divided by the 2-norm of the user-supplied solution
C is less than TOL.
C TOL :INOUT Double Precision.
C Convergence criterion, as described above. (Reset if IERR=4.)
C ITMAX :IN Integer.
C Maximum number of iterations.
C ITER :OUT Integer.
C Number of iterations required to reach convergence, or
C ITMAX+1 if convergence criterion could not be achieved in
C ITMAX iterations.
C ERR :OUT Double Precision.
C Error estimate of error in final approximate solution, as
C defined by ITOL.
C IERR :OUT Integer.
C Return error flag.
C IERR = 0 => All went well.
C IERR = 1 => Insufficient space allocated for WORK or IWORK.
C IERR = 2 => Method failed to converge in ITMAX steps.
C IERR = 3 => Error in user input.
C Check input values of N, ITOL.
C IERR = 4 => User error tolerance set too tight.
C Reset to 500*D1MACH(3). Iteration proceeded.
C IERR = 5 => Breakdown of the method detected.
C (r0,r) approximately 0.
C IERR = 6 => Stagnation of the method detected.
C (r0,v) approximately 0.
C IUNIT :IN Integer.
C Unit number on which to write the error at each iteration,
C if this is desired for monitoring convergence. If unit
C number is 0, no writing will occur.
C R :WORK Double Precision R(N).
C R0 :WORK Double Precision R0(N).
C P :WORK Double Precision P(N).
C Q :WORK Double Precision Q(N).
C U :WORK Double Precision U(N).
C V1 :WORK Double Precision V1(N).
C V2 :WORK Double Precision V2(N).
C Double Precision arrays used for workspace.
C RWORK :WORK Double Precision RWORK(USER DEFINED).
C Double Precision array that can be used for workspace in
C MSOLVE.
C IWORK :WORK Integer IWORK(USER DEFINED).
C Integer array that can be used for workspace in MSOLVE.
C
C *Description
C This routine does not care what matrix data structure is
C used for A and M. It simply calls the MATVEC and MSOLVE
C routines, with the arguments as described above. The user
C could write any type of structure and the appropriate MATVEC
C and MSOLVE routines. It is assumed that A is stored in the
C IA, JA, A arrays in some fashion and that M (or INV(M)) is
C stored in IWORK and RWORK in some fashion. The SLAP
C routines DSDBCG and DSLUCS are examples of this procedure.
C
C Two examples of matrix data structures are the: 1) SLAP
C Triad format and 2) SLAP Column format.
C
C =================== S L A P Triad format ===================
C
C In this format only the non-zeros are stored. They may
C appear in *ANY* order. The user supplies three arrays of
C length NELT, where NELT is the number of non-zeros in the
C matrix: (IA(NELT), JA(NELT), A(NELT)). For each non-zero
C the user puts the row and column index of that matrix
C element in the IA and JA arrays. The value of the non-zero
C matrix element is placed in the corresponding location of
C the A array. This is an extremely easy data structure to
C generate. On the other hand it is not too efficient on
C vector computers for the iterative solution of linear
C systems. Hence, SLAP changes this input data structure to
C the SLAP Column format for the iteration (but does not
C change it back).
C
C Here is an example of the SLAP Triad storage format for a
C 5x5 Matrix. Recall that the entries may appear in any order.
C
C 5x5 Matrix SLAP Triad format for 5x5 matrix on left.
C 1 2 3 4 5 6 7 8 9 10 11
C |11 12 0 0 15| A: 51 12 11 33 15 53 55 22 35 44 21
C |21 22 0 0 0| IA: 5 1 1 3 1 5 5 2 3 4 2
C | 0 0 33 0 35| JA: 1 2 1 3 5 3 5 2 5 4 1
C | 0 0 0 44 0|
C |51 0 53 0 55|
C
C =================== S L A P Column format ==================
C
C In this format the non-zeros are stored counting down
C columns (except for the diagonal entry, which must appear
C first in each "column") and are stored in the double pre-
C cision array A. In other words, for each column in the
C matrix first put the diagonal entry in A. Then put in the
C other non-zero elements going down the column (except the
C diagonal) in order. The IA array holds the row index for
C each non-zero. The JA array holds the offsets into the IA,
C A arrays for the beginning of each column. That is,
C IA(JA(ICOL)),A(JA(ICOL)) are the first elements of the ICOL-
C th column in IA and A, and IA(JA(ICOL+1)-1), A(JA(ICOL+1)-1)
C are the last elements of the ICOL-th column. Note that we
C always have JA(N+1)=NELT+1, where N is the number of columns
C in the matrix and NELT is the number of non-zeros in the
C matrix.
C
C Here is an example of the SLAP Column storage format for a
C 5x5 Matrix (in the A and IA arrays '|' denotes the end of a
C column):
C
C 5x5 Matrix SLAP Column format for 5x5 matrix on left.
C 1 2 3 4 5 6 7 8 9 10 11
C |11 12 0 0 15| A: 11 21 51 | 22 12 | 33 53 | 44 | 55 15 35
C |21 22 0 0 0| IA: 1 2 5 | 2 1 | 3 5 | 4 | 5 1 3
C | 0 0 33 0 35| JA: 1 4 6 8 9 12
C | 0 0 0 44 0|
C |51 0 53 0 55|
C
C *Cautions:
C This routine will attempt to write to the Fortran logical output
C unit IUNIT, if IUNIT .ne. 0. Thus, the user must make sure that
C this logical unit is attached to a file or terminal before calling
C this routine with a non-zero value for IUNIT. This routine does
C not check for the validity of a non-zero IUNIT unit number.
C
C***SEE ALSO DSDCGS, DSLUCS
C***REFERENCES 1. P. Sonneveld, CGS, a fast Lanczos-type solver
C for nonsymmetric linear systems, Delft University
C of Technology Report 84-16, Department of Mathe-
C matics and Informatics, Delft, The Netherlands.
C 2. E. F. Kaasschieter, The solution of non-symmetric
C linear systems by biconjugate gradients or conjugate
C gradients squared, Delft University of Technology
C Report 86-21, Department of Mathematics and Informa-
C tics, Delft, The Netherlands.
C 3. Mark K. Seager, A SLAP for the Masses, in
C G. F. Carey, Ed., Parallel Supercomputing: Methods,
C Algorithms and Applications, Wiley, 1989, pp.135-155.
C***ROUTINES CALLED D1MACH, DAXPY, DDOT, ISDCGS
C***REVISION HISTORY (YYMMDD)
C 890404 DATE WRITTEN
C 890404 Previous REVISION DATE
C 890915 Made changes requested at July 1989 CML Meeting. (MKS)
C 890921 Removed TeX from comments. (FNF)
C 890922 Numerous changes to prologue to make closer to SLATEC
C standard. (FNF)
C 890929 Numerous changes to reduce SP/DP differences. (FNF)
C 891004 Added new reference.
C 910411 Prologue converted to Version 4.0 format. (BAB)
C 910502 Removed MATVEC and MSOLVE from ROUTINES CALLED list. (FNF)
C 920407 COMMON BLOCK renamed DSLBLK. (WRB)
C 920511 Added complete declaration section. (WRB)
C 920929 Corrected format of references. (FNF)
C 921019 Changed 500.0 to 500 to reduce SP/DP differences. (FNF)
C 921113 Corrected C***CATEGORY line. (FNF)
C***END PROLOGUE DCGS
C .. Scalar Arguments ..
DOUBLE PRECISION ERR, TOL
INTEGER IERR, ISYM, ITER, ITMAX, ITOL, IUNIT, N, NELT
C .. Array Arguments ..
DOUBLE PRECISION A(NELT), B(N), P(N), Q(N), R(N), R0(N), RWORK(*),
+ U(N), V1(N), V2(N), X(N)
INTEGER IA(NELT), IWORK(*), JA(NELT)
C .. Subroutine Arguments ..
EXTERNAL MATVEC, MSOLVE
C .. Local Scalars ..
DOUBLE PRECISION AK, AKM, BK, BNRM, FUZZ, RHON, RHONM1, SIGMA,
+ SOLNRM, TOLMIN
INTEGER I, K
C .. External Functions ..
DOUBLE PRECISION D1MACH, DDOT
INTEGER ISDCGS
EXTERNAL D1MACH, DDOT, ISDCGS
C .. External Subroutines ..
EXTERNAL DAXPY
C .. Intrinsic Functions ..
INTRINSIC ABS
C***FIRST EXECUTABLE STATEMENT DCGS
C
C Check some of the input data.
C
ITER = 0
IERR = 0
IF( N.LT.1 ) THEN
IERR = 3
RETURN
ENDIF
TOLMIN = 500*D1MACH(3)
IF( TOL.LT.TOLMIN ) THEN
TOL = TOLMIN
IERR = 4
ENDIF
C
C Calculate initial residual and pseudo-residual, and check
C stopping criterion.
CALL MATVEC(N, X, R, NELT, IA, JA, A, ISYM)
DO 10 I = 1, N
V1(I) = R(I) - B(I)
10 CONTINUE
CALL MSOLVE(N, V1, R, NELT, IA, JA, A, ISYM, RWORK, IWORK)
C
IF( ISDCGS(N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MSOLVE,
$ ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT, R, R0, P, Q,
$ U, V1, V2, RWORK, IWORK, AK, BK, BNRM, SOLNRM) .NE. 0 )
$ GO TO 200
IF( IERR.NE.0 ) RETURN
C
C Set initial values.
C
FUZZ = D1MACH(3)**2
DO 20 I = 1, N
R0(I) = R(I)
20 CONTINUE
RHONM1 = 1
C
C ***** ITERATION LOOP *****
C
DO 100 K=1,ITMAX
ITER = K
C
C Calculate coefficient BK and direction vectors U, V and P.
RHON = DDOT(N, R0, 1, R, 1)
IF( ABS(RHONM1).LT.FUZZ ) GOTO 998
BK = RHON/RHONM1
IF( ITER.EQ.1 ) THEN
DO 30 I = 1, N
U(I) = R(I)
P(I) = R(I)
30 CONTINUE
ELSE
DO 40 I = 1, N
U(I) = R(I) + BK*Q(I)
V1(I) = Q(I) + BK*P(I)
40 CONTINUE
DO 50 I = 1, N
P(I) = U(I) + BK*V1(I)
50 CONTINUE
ENDIF
C
C Calculate coefficient AK, new iterate X, Q
CALL MATVEC(N, P, V2, NELT, IA, JA, A, ISYM)
CALL MSOLVE(N, V2, V1, NELT, IA, JA, A, ISYM, RWORK, IWORK)
SIGMA = DDOT(N, R0, 1, V1, 1)
IF( ABS(SIGMA).LT.FUZZ ) GOTO 999
AK = RHON/SIGMA
AKM = -AK
DO 60 I = 1, N
Q(I) = U(I) + AKM*V1(I)
60 CONTINUE
DO 70 I = 1, N
V1(I) = U(I) + Q(I)
70 CONTINUE
C X = X - ak*V1.
CALL DAXPY( N, AKM, V1, 1, X, 1 )
C -1
C R = R - ak*M *A*V1
CALL MATVEC(N, V1, V2, NELT, IA, JA, A, ISYM)
CALL MSOLVE(N, V2, V1, NELT, IA, JA, A, ISYM, RWORK, IWORK)
CALL DAXPY( N, AKM, V1, 1, R, 1 )
C
C check stopping criterion.
IF( ISDCGS(N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MSOLVE,
$ ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT, R, R0, P, Q,
$ U, V1, V2, RWORK, IWORK, AK, BK, BNRM, SOLNRM) .NE. 0 )
$ GO TO 200
C
C Update RHO.
RHONM1 = RHON
100 CONTINUE
C
C ***** end of loop *****
C Stopping criterion not satisfied.
ITER = ITMAX + 1
IERR = 2
200 RETURN
C
C Breakdown of method detected.
998 IERR = 5
RETURN
C
C Stagnation of method detected.
999 IERR = 6
RETURN
C------------- LAST LINE OF DCGS FOLLOWS ----------------------------
END