Actual source code: ex6f.F

petsc-3.8.4 2018-03-24
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  1: !
  2: !  Description: This example demonstrates repeated linear solves as
  3: !  well as the use of different preconditioner and linear system
  4: !  matrices.  This example also illustrates how to save PETSc objects
  5: !  in common blocks.
  6: !
  7: !/*T
  8: !  Concepts: KSP^repeatedly solving linear systems;
  9: !  Concepts: KSP^different matrices for linear system and preconditioner;
 10: !  Processors: n
 11: !T*/
 12: !

 14:       program main
 15:  #include <petsc/finclude/petscksp.h>
 16:       use petscksp
 17:       implicit none

 19: !  Variables:
 20: !
 21: !  A       - matrix that defines linear system
 22: !  ksp    - KSP context
 23: !  ksp     - KSP context
 24: !  x, b, u - approx solution, RHS, exact solution vectors
 25: !
 26:       Vec     x,u,b
 27:       Mat     A
 28:       KSP    ksp
 29:       PetscInt i,j,II,JJ,m,n
 30:       PetscInt Istart,Iend
 31:       PetscInt nsteps,one
 32:       PetscErrorCode ierr
 33:       PetscBool  flg
 34:       PetscScalar  v


 37:       call PetscInitialize(PETSC_NULL_CHARACTER,ierr)
 38:       if (ierr .ne. 0) then
 39:         print*,'Unable to initialize PETSc'
 40:         stop
 41:       endif
 42:       m      = 3
 43:       n      = 3
 44:       nsteps = 2
 45:       one    = 1
 46:       call PetscOptionsGetInt(PETSC_NULL_OPTIONS,PETSC_NULL_CHARACTER,    &
 47:      &                        '-m',m,flg,ierr)
 48:       call PetscOptionsGetInt(PETSC_NULL_OPTIONS,PETSC_NULL_CHARACTER,    &
 49:      &                        '-n',n,flg,ierr)
 50:       call PetscOptionsGetInt(PETSC_NULL_OPTIONS,PETSC_NULL_CHARACTER,    &
 51:      &                        '-nsteps',nsteps,flg,ierr)

 53: !  Create parallel matrix, specifying only its global dimensions.
 54: !  When using MatCreate(), the matrix format can be specified at
 55: !  runtime. Also, the parallel partitioning of the matrix is
 56: !  determined by PETSc at runtime.

 58:       call MatCreate(PETSC_COMM_WORLD,A,ierr)
 59:       call MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m*n,m*n,ierr)
 60:       call MatSetFromOptions(A,ierr)
 61:       call MatSetUp(A,ierr)

 63: !  The matrix is partitioned by contiguous chunks of rows across the
 64: !  processors.  Determine which rows of the matrix are locally owned.

 66:       call MatGetOwnershipRange(A,Istart,Iend,ierr)

 68: !  Set matrix elements.
 69: !   - Each processor needs to insert only elements that it owns
 70: !     locally (but any non-local elements will be sent to the
 71: !     appropriate processor during matrix assembly).
 72: !   - Always specify global rows and columns of matrix entries.

 74:       do 10, II=Istart,Iend-1
 75:         v = -1.0
 76:         i = II/n
 77:         j = II - i*n
 78:         if (i.gt.0) then
 79:           JJ = II - n
 80:           call MatSetValues(A,one,II,one,JJ,v,ADD_VALUES,ierr)
 81:         endif
 82:         if (i.lt.m-1) then
 83:           JJ = II + n
 84:           call MatSetValues(A,one,II,one,JJ,v,ADD_VALUES,ierr)
 85:         endif
 86:         if (j.gt.0) then
 87:           JJ = II - 1
 88:           call MatSetValues(A,one,II,one,JJ,v,ADD_VALUES,ierr)
 89:         endif
 90:         if (j.lt.n-1) then
 91:           JJ = II + 1
 92:           call MatSetValues(A,one,II,one,JJ,v,ADD_VALUES,ierr)
 93:         endif
 94:         v = 4.0
 95:         call  MatSetValues(A,one,II,one,II,v,ADD_VALUES,ierr)
 96:  10   continue

 98: !  Assemble matrix, using the 2-step process:
 99: !       MatAssemblyBegin(), MatAssemblyEnd()
100: !  Computations can be done while messages are in transition
101: !  by placing code between these two statements.

103:       call MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr)
104:       call MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr)

106: !  Create parallel vectors.
107: !   - When using VecCreate(), the parallel partitioning of the vector
108: !     is determined by PETSc at runtime.
109: !   - Note: We form 1 vector from scratch and then duplicate as needed.

111:       call VecCreate(PETSC_COMM_WORLD,u,ierr)
112:       call VecSetSizes(u,PETSC_DECIDE,m*n,ierr)
113:       call VecSetFromOptions(u,ierr)
114:       call VecDuplicate(u,b,ierr)
115:       call VecDuplicate(b,x,ierr)

117: !  Create linear solver context

119:       call KSPCreate(PETSC_COMM_WORLD,ksp,ierr)

121: !  Set runtime options (e.g., -ksp_type <type> -pc_type <type>)

123:       call KSPSetFromOptions(ksp,ierr)

125: !  Solve several linear systems in succession

127:       do 100 i=1,nsteps
128:          call solve1(ksp,A,x,b,u,i,nsteps,ierr)
129:  100  continue

131: !  Free work space.  All PETSc objects should be destroyed when they
132: !  are no longer needed.

134:       call VecDestroy(u,ierr)
135:       call VecDestroy(x,ierr)
136:       call VecDestroy(b,ierr)
137:       call MatDestroy(A,ierr)
138:       call KSPDestroy(ksp,ierr)

140:       call PetscFinalize(ierr)
141:       end

143: ! -----------------------------------------------------------------------
144: !
145:       subroutine solve1(ksp,A,x,b,u,count,nsteps,ierr)
146:       use petscksp
147:       implicit none

149: !
150: !   solve1 - This routine is used for repeated linear system solves.
151: !   We update the linear system matrix each time, but retain the same
152: !   preconditioning matrix for all linear solves.
153: !
154: !      A - linear system matrix
155: !      A2 - preconditioning matrix
156: !
157:       PetscScalar  v,val
158:       PetscInt II,Istart,Iend
159:       PetscInt count,nsteps,one
160:       PetscErrorCode ierr
161:       Mat     A
162:       KSP     ksp
163:       Vec     x,b,u

165: ! Use common block to retain matrix between successive subroutine calls
166:       Mat              A2
167:       PetscMPIInt      rank
168:       PetscBool        pflag
169:       common /my_data/ A2,pflag,rank

171:       one = 1
172: ! First time thorough: Create new matrix to define the linear system
173:       if (count .eq. 1) then
174:         call MPI_Comm_rank(PETSC_COMM_WORLD,rank,ierr)
175:         pflag = .false.
176:         call PetscOptionsHasName(PETSC_NULL_OPTIONS,                          &
177:      &               PETSC_NULL_CHARACTER,'-mat_view',pflag,ierr)
178:         if (pflag) then
179:           if (rank .eq. 0) write(6,100)
180:           call flush(6)
181:         endif
182:         call MatConvert(A,MATSAME,MAT_INITIAL_MATRIX,A2,ierr)
183: ! All other times: Set previous solution as initial guess for next solve.
184:       else
185:         call KSPSetInitialGuessNonzero(ksp,PETSC_TRUE,ierr)
186:       endif

188: ! Alter the matrix A a bit
189:       call MatGetOwnershipRange(A,Istart,Iend,ierr)
190:       do 20, II=Istart,Iend-1
191:         v = 2.0
192:         call MatSetValues(A,one,II,one,II,v,ADD_VALUES,ierr)
193:  20   continue
194:       call MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr)
195:       if (pflag) then
196:         if (rank .eq. 0) write(6,110)
197:         call flush(6)
198:       endif
199:       call MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr)

201: ! Set the exact solution; compute the right-hand-side vector
202:       val = 1.0*real(count)
203:       call VecSet(u,val,ierr)
204:       call MatMult(A,u,b,ierr)

206: ! Set operators, keeping the identical preconditioner matrix for
207: ! all linear solves.  This approach is often effective when the
208: ! linear systems do not change very much between successive steps.
209:       call KSPSetReusePreconditioner(ksp,PETSC_TRUE,ierr)
210:       call KSPSetOperators(ksp,A,A2,ierr)

212: ! Solve linear system
213:       call KSPSolve(ksp,b,x,ierr)

215: ! Destroy the preconditioner matrix on the last time through
216:       if (count .eq. nsteps) call MatDestroy(A2,ierr)

218:  100  format('previous matrix: preconditioning')
219:  110  format('next matrix: defines linear system')

221:       end