123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375 |
- *DECK SBCG
- SUBROUTINE SBCG (N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MTTVEC,
- + MSOLVE, MTSOLV, ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT, R, Z,
- + P, RR, ZZ, PP, DZ, RWORK, IWORK)
- C***BEGIN PROLOGUE SBCG
- C***PURPOSE Preconditioned BiConjugate Gradient Sparse Ax = b Solver.
- C Routine to solve a Non-Symmetric linear system Ax = b
- C using the Preconditioned BiConjugate Gradient method.
- C***LIBRARY SLATEC (SLAP)
- C***CATEGORY D2A4, D2B4
- C***TYPE SINGLE PRECISION (SBCG-S, DBCG-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 REAL B(N), X(N), A(NELT), TOL, ERR, R(N), Z(N), P(N)
- C REAL RR(N), ZZ(N), PP(N), DZ(N)
- C REAL RWORK(USER DEFINED)
- C EXTERNAL MATVEC, MTTVEC, MSOLVE, MTSOLV
- C
- C CALL SBCG(N, B, X, NELT, IA, JA, A, ISYM, MATVEC, MTTVEC,
- C $ MSOLVE, MTSOLV, ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT,
- C $ R, Z, P, RR, ZZ, PP, DZ, RWORK, IWORK)
- C
- C *Arguments:
- C N :IN Integer
- C Order of the Matrix.
- C B :IN Real B(N).
- C Right-hand side vector.
- C X :INOUT Real 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 Real A(NELT).
- C These arrays contain the matrix data structure for A.
- C It could take any form. See "Description", below, for more
- C 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 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 MTTVEC, 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, 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 real array that can be used
- C to pass necessary preconditioning information and/or
- C workspace to MSOLVE. IWORK is an integer work array for the
- C same purpose as RWORK.
- C MTSOLV :EXT External.
- C Name of a routine which solves a linear system M'ZZ = RR for
- C ZZ given RR with the preconditioning matrix M (M is supplied
- C via RWORK and IWORK arrays). The name of the MTSOLV routine
- C must be declared external in the calling program. The call-
- C ing sequence to MTSOLV is:
- C CALL MTSOLV(N, RR, ZZ, NELT, IA, JA, A, ISYM, RWORK, IWORK)
- C Where N is the number of unknowns, RR is the right-hand side
- C vector, and ZZ 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 real array that can be used
- C to pass necessary preconditioning information and/or
- C workspace to MTSOLV. IWORK is an integer work array for the
- C 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 /SSLBLK/ 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 /SSLBLK/ 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 Real.
- 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 Real.
- 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*R1MACH(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 Real R(N).
- C Z :WORK Real Z(N).
- C P :WORK Real P(N).
- C RR :WORK Real RR(N).
- C ZZ :WORK Real ZZ(N).
- C PP :WORK Real PP(N).
- C DZ :WORK Real DZ(N).
- C Real arrays used for workspace.
- C RWORK :WORK Real RWORK(USER DEFINED).
- C Real array that can be used for workspace in MSOLVE
- C and MTSOLV.
- C IWORK :WORK Integer IWORK(USER DEFINED).
- C Integer array that can be used for workspace in MSOLVE
- C and MTSOLV.
- C
- C *Description
- C This routine does not care what matrix data structure is used
- C for A and M. It simply calls MATVEC, MTTVEC, MSOLVE, MTSOLV
- C routines, with arguments as above. The user could write any
- C type of structure, and appropriate MATVEC, MSOLVE, MTTVEC,
- C and MTSOLV 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 SSDBCG and SSLUBC 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 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 real array A.
- C In other words, for each column in the matrix put the
- C diagonal entry in A. Then put in the other non-zero
- C elements going down the column (except the diagonal) in
- C order. The IA array holds the row index for each non-zero.
- C The JA array holds the offsets into the IA, A arrays for the
- C beginning of each column. That is, IA(JA(ICOL)),
- C A(JA(ICOL)) points to the beginning of the ICOL-th column in
- C IA and A. IA(JA(ICOL+1)-1), A(JA(ICOL+1)-1) points to the
- C end of the ICOL-th column. Note that we always have JA(N+1)
- C = NELT+1, where N is the number of columns in the matrix and
- C NELT is the number of non-zeros in the 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 SSDBCG, SSLUBC
- 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 ISSBCG, R1MACH, SAXPY, SCOPY, SDOT
- C***REVISION HISTORY (YYMMDD)
- C 871119 DATE WRITTEN
- C 881213 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, MSOLVE, MTSOLV from ROUTINES
- C CALLED list. (FNF)
- C 920407 COMMON BLOCK renamed SSLBLK. (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 SBCG
- C .. Scalar Arguments ..
- REAL ERR, TOL
- INTEGER IERR, ISYM, ITER, ITMAX, ITOL, IUNIT, N, NELT
- C .. Array Arguments ..
- REAL A(NELT), B(N), DZ(N), P(N), PP(N), R(N), RR(N), RWORK(*),
- + X(N), Z(N), ZZ(N)
- INTEGER IA(NELT), IWORK(*), JA(NELT)
- C .. Subroutine Arguments ..
- EXTERNAL MATVEC, MSOLVE, MTSOLV, MTTVEC
- C .. Local Scalars ..
- REAL AK, AKDEN, BK, BKDEN, BKNUM, BNRM, FUZZ, SOLNRM, TOLMIN
- INTEGER I, K
- C .. External Functions ..
- REAL R1MACH, SDOT
- INTEGER ISSBCG
- EXTERNAL R1MACH, SDOT, ISSBCG
- C .. External Subroutines ..
- EXTERNAL SAXPY, SCOPY
- C .. Intrinsic Functions ..
- INTRINSIC ABS
- C***FIRST EXECUTABLE STATEMENT SBCG
- C
- C Check some of the input data.
- C
- ITER = 0
- IERR = 0
- IF( N.LT.1 ) THEN
- IERR = 3
- RETURN
- ENDIF
- FUZZ = R1MACH(3)
- TOLMIN = 500*FUZZ
- FUZZ = FUZZ*FUZZ
- 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
- R(I) = B(I) - R(I)
- RR(I) = R(I)
- 10 CONTINUE
- CALL MSOLVE(N, R, Z, NELT, IA, JA, A, ISYM, RWORK, IWORK)
- CALL MTSOLV(N, RR, ZZ, NELT, IA, JA, A, ISYM, RWORK, IWORK)
- C
- IF( ISSBCG(N, B, X, NELT, IA, JA, A, ISYM, MSOLVE, ITOL, TOL,
- $ ITMAX, ITER, ERR, IERR, IUNIT, R, Z, P, RR, ZZ, PP,
- $ DZ, RWORK, IWORK, AK, BK, BNRM, SOLNRM) .NE. 0 )
- $ GO TO 200
- IF( IERR.NE.0 ) RETURN
- C
- C ***** iteration loop *****
- C
- DO 100 K=1,ITMAX
- ITER = K
- C
- C Calculate coefficient BK and direction vectors P and PP.
- BKNUM = SDOT(N, Z, 1, RR, 1)
- IF( ABS(BKNUM).LE.FUZZ ) THEN
- IERR = 6
- RETURN
- ENDIF
- IF(ITER .EQ. 1) THEN
- CALL SCOPY(N, Z, 1, P, 1)
- CALL SCOPY(N, ZZ, 1, PP, 1)
- ELSE
- BK = BKNUM/BKDEN
- DO 20 I = 1, N
- P(I) = Z(I) + BK*P(I)
- PP(I) = ZZ(I) + BK*PP(I)
- 20 CONTINUE
- ENDIF
- BKDEN = BKNUM
- C
- C Calculate coefficient AK, new iterate X, new residuals R and
- C RR, and new pseudo-residuals Z and ZZ.
- CALL MATVEC(N, P, Z, NELT, IA, JA, A, ISYM)
- AKDEN = SDOT(N, PP, 1, Z, 1)
- AK = BKNUM/AKDEN
- IF( ABS(AKDEN).LE.FUZZ ) THEN
- IERR = 6
- RETURN
- ENDIF
- CALL SAXPY(N, AK, P, 1, X, 1)
- CALL SAXPY(N, -AK, Z, 1, R, 1)
- CALL MTTVEC(N, PP, ZZ, NELT, IA, JA, A, ISYM)
- CALL SAXPY(N, -AK, ZZ, 1, RR, 1)
- CALL MSOLVE(N, R, Z, NELT, IA, JA, A, ISYM, RWORK, IWORK)
- CALL MTSOLV(N, RR, ZZ, NELT, IA, JA, A, ISYM, RWORK, IWORK)
- C
- C check stopping criterion.
- IF( ISSBCG(N, B, X, NELT, IA, JA, A, ISYM, MSOLVE, ITOL, TOL,
- $ ITMAX, ITER, ERR, IERR, IUNIT, R, Z, P, RR, ZZ,
- $ PP, DZ, RWORK, IWORK, AK, BK, BNRM, SOLNRM) .NE. 0 )
- $ GO TO 200
- C
- 100 CONTINUE
- C
- C ***** end of loop *****
- C
- C stopping criterion not satisfied.
- ITER = ITMAX + 1
- IERR = 2
- C
- 200 RETURN
- C------------- LAST LINE OF SBCG FOLLOWS ----------------------------
- END
|