SLATEC Routines --- DCGN ---
*DECK DCGN
SUBROUTINE DCGN (N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MTTVEC,
+ MSOLVE, ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT, R, Z, P, ATP,
+ ATZ, DZ, ATDZ, RWORK, IWORK)
C***BEGIN PROLOGUE DCGN
C***PURPOSE Preconditioned CG Sparse Ax=b Solver for Normal Equations.
C Routine to solve a general linear system Ax = b using the
C Preconditioned Conjugate Gradient method applied to the
C normal equations AA'y = b, x=A'y.
C***LIBRARY SLATEC (SLAP)
C***CATEGORY D2A4, D2B4
C***TYPE DOUBLE PRECISION (SCGN-S, DCGN-D)
C***KEYWORDS ITERATIVE PRECONDITION, NON-SYMMETRIC LINEAR SYSTEM SOLVE,
C NORMAL EQUATIONS., 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), Z(N)
C DOUBLE PRECISION P(N), ATP(N), ATZ(N), DZ(N), ATDZ(N)
C DOUBLE PRECISION RWORK(USER DEFINED)
C EXTERNAL MATVEC, MTTVEC, MSOLVE
C
C CALL DCGN(N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MTTVEC,
C $ MSOLVE, ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT, R,
C $ Z, P, ATP, ATZ, DZ, ATDZ, 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 y = A*X given A and X. The name of the MATVEC routine must
C be declared external in the calling program. The calling
C sequence to 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
C upon return X is an input vector, NELT is the number of
C non-zeros in the SLAP-Column IA, JA, A storage for the matrix
C A. ISYM is a flag which, if non-zero, denotes that A is
C symmetric and only the lower or upper triangle is stored.
C MTTVEC :EXT External.
C Name of a routine which performs the matrix transpose vector
C multiply y = A'*X given A and X (where ' denotes transpose).
C The name of the MTTVEC routine must be declared external in
C the calling program. The calling sequence to MTTVEC is the
C same as that for MATVEC, viz.:
C CALL MTTVEC( N, X, Y, NELT, IA, JA, A, ISYM )
C Where N is the number of unknowns, Y is the product A'*X
C upon return X is an input vector, NELT is the number of
C non-zeros in the SLAP-Column IA, JA, A storage for the matrix
C A. ISYM is a flag which, if non-zero, denotes that A is
C symmetric and only the lower or upper triangle is stored.
C MSOLVE :EXT External.
C Name of a routine which solves a linear system MZ = R for
C Z given R with the preconditioning matrix M (M is supplied via
C RWORK and IWORK arrays). The name of the MSOLVE routine must
C be declared external in the calling program. The calling
C sequence to 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 and
C ISYM are defined as above. RWORK is a double precision array
C that can be used to pass necessary preconditioning information
C and/or workspace to MSOLVE. IWORK is an integer work array
C for 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 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 is the inverse of the
C diagonal of A.
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. Note that this requires the user to set up
C the "COMMON /DSLBLK/ SOLN(LENGTH)" in the calling routine.
C The routine with this declaration should be loaded before the
C stop test so that the correct length is used by the loader.
C This procedure is not standard Fortran and may not work
C correctly on your system (although it has worked on every
C system the authors have tried). If ITOL is not 11 then this
C common block is indeed standard Fortran.
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 => Preconditioning matrix, M, is not positive
C definite. (r,z) < 0.
C IERR = 6 => Matrix A is not positive definite. (p,Ap) < 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 Z :WORK Double Precision Z(N).
C P :WORK Double Precision P(N).
C ATP :WORK Double Precision ATP(N).
C ATZ :WORK Double Precision ATZ(N).
C DZ :WORK Double Precision DZ(N).
C ATDZ :WORK Double Precision ATDZ(N).
C Double Precision arrays used for workspace.
C RWORK :WORK Double Precision RWORK(USER DEFINED).
C Double Precision array that can be used by MSOLVE.
C IWORK :WORK Integer IWORK(USER DEFINED).
C Integer array that can be used by MSOLVE.
C
C *Description:
C This routine applies the preconditioned conjugate gradient
C (PCG) method to a non-symmetric system of equations Ax=b. To
C do this the normal equations are solved:
C AA' y = b, where x = A'y.
C In PCG method the iteration count is determined by condition
C -1
C number of the matrix (M A). In the situation where the
C normal equations are used to solve a non-symmetric system
C the condition number depends on AA' and should therefore be
C much worse than that of A. This is the conventional wisdom.
C When one has a good preconditioner for AA' this may not hold.
C The latter is the situation when DCGN should be tried.
C
C If one is trying to solve a symmetric system, SCG should be
C used instead.
C
C This routine does not care what matrix data structure is
C used for A and M. It simply calls MATVEC, MTTVEC and MSOLVE
C routines, with arguments as described above. The user could
C write any type of structure, and appropriate MATVEC, MTTVEC
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 SSDCGN and SSLUCN 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 DSDCGN, DSLUCN, ISDCGN
C***REFERENCES 1. 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, DCOPY, DDOT, ISDCGN
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, MTTVEC and MSOLVE from ROUTINES CALLED
C list. (FNF)
C 920407 COMMON BLOCK renamed DSLBLK. (WRB)
C 920511 Added complete declaration section. (WRB)
C 920929 Corrected format of reference. (FNF)
C 921019 Changed 500.0 to 500 to reduce SP/DP differences. (FNF)
C 921113 Corrected C***CATEGORY line. (FNF)
C***END PROLOGUE DCGN