subroutine atx_cr ( n, nz_num, ia, ja, a, x, w ) !*****************************************************************************80 ! !! ATX_CR computes A'*x for a matrix stored in sparse compressed row form. ! ! Discussion: ! ! The Sparse Compressed Row storage format is used. ! ! The matrix A is assumed to be sparse. To save on storage, only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA[I] through IA[I+1]-1. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 17 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(N+1), JA(NZ_NUM), the row and column ! indices of the matrix values. The row vector has been compressed. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input, real ( kind = 8 ) X(N), the vector to be multiplied by A'. ! ! Output, real ( kind = 8 ) W(N), the value of A'*X. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k integer ( kind = 4 ) k1 integer ( kind = 4 ) k2 real ( kind = 8 ) w(n) real ( kind = 8 ) x(n) w(1:n) = 0.0D+00 do i = 1, n k1 = ia(i) k2 = ia(i+1) - 1 w(ja(k1:k2)) = w(ja(k1:k2)) + a(k1:k2) * x(i) end do return end subroutine atx_st ( n, nz_num, ia, ja, a, x, w ) !*****************************************************************************80 ! !! ATX_ST computes A'*x for a matrix stored in sparset triplet form. ! ! Discussion: ! ! The matrix A is assumed to be sparse. To save on storage, only ! the nonzero entries of A are stored. For instance, the K-th nonzero ! entry in the matrix is stored by: ! ! A(K) = value of entry, ! IA(K) = row of entry, ! JA(K) = column of entry. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 08 August 2006 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(NZ_NUM), JA(NZ_NUM), the row and column ! indices of the matrix values. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input, real ( kind = 8 ) X(N), the vector to be multiplied by A'. ! ! Output, real ( kind = 8 ) W(N), the value of A'*X. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) integer ( kind = 4 ) i integer ( kind = 4 ) ia(nz_num) integer ( kind = 4 ) j integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k real ( kind = 8 ) w(n) real ( kind = 8 ) x(n) w(1:n) = 0.0D+00 do k = 1, nz_num i = ia(k) j = ja(k) w(j) = w(j) + a(k) * x(i) end do return end subroutine ax_cr ( n, nz_num, ia, ja, a, x, w ) !*****************************************************************************80 ! !! AX_CR computes A*x for a matrix stored in sparse compressed row form. ! ! Discussion: ! ! The Sparse Compressed Row storage format is used. ! ! The matrix A is assumed to be sparse. To save on storage, only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA[I] through IA[I+1]-1. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 17 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(N+1), JA(NZ_NUM), the row and column ! indices of the matrix values. The row vector has been compressed. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input, real ( kind = 8 ) X(N), the vector to be multiplied by A. ! ! Output, real ( kind = 8 ) W(N), the value of A*X. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k integer ( kind = 4 ) k1 integer ( kind = 4 ) k2 real ( kind = 8 ) w(n) real ( kind = 8 ) x(n) w(1:n) = 0.0D+00 do i = 1, n k1 = ia(i) k2 = ia(i+1) - 1 w(i) = w(i) + dot_product ( a(k1:k2), x(ja(k1:k2)) ) end do return end subroutine ax_st ( n, nz_num, ia, ja, a, x, w ) !*****************************************************************************80 ! !! AX_ST computes A*x for a matrix stored in sparset triplet form. ! ! Discussion: ! ! The matrix A is assumed to be sparse. To save on storage, only ! the nonzero entries of A are stored. For instance, the K-th nonzero ! entry in the matrix is stored by: ! ! A(K) = value of entry, ! IA(K) = row of entry, ! JA(K) = column of entry. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 08 August 2006 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(NZ_NUM), JA(NZ_NUM), the row and column ! indices of the matrix values. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input, real ( kind = 8 ) X(N), the vector to be multiplied by A. ! ! Output, real ( kind = 8 ) W(N), the value of A*X. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) integer ( kind = 4 ) i integer ( kind = 4 ) ia(nz_num) integer ( kind = 4 ) j integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k real ( kind = 8 ) w(n) real ( kind = 8 ) x(n) w(1:n) = 0.0D+00 do k = 1, nz_num i = ia(k) j = ja(k) w(i) = w(i) + a(k) * x(j) end do return end subroutine diagonal_pointer_cr ( n, nz_num, ia, ja, ua ) !*****************************************************************************80 ! !! DIAGONAL_POINTER_CR finds diagonal entries in a sparse compressed row matrix. ! ! Discussion: ! ! The matrix A is assumed to be stored in compressed row format. Only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA[I] through IA[I+1]-1. ! ! The array UA can be used to locate the diagonal elements of the matrix. ! ! It is assumed that every row of the matrix includes a diagonal element, ! and that the elements of each row have been ascending sorted. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 18 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(N+1), JA(NZ_NUM), the row and column ! indices of the matrix values. The row vector has been compressed. ! On output, the order of the entries of JA may have changed because of ! the sorting. ! ! Output, integer ( kind = 4 ) UA(N), the index of the diagonal element ! of each row. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) k integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) ua(n) ua(1:n) = -1 do i = 1, n do k = ia(i), ia(i+1) - 1 if ( ja(k) == i ) then ua(i) = k end if end do end do return end subroutine ilu_cr ( n, nz_num, ia, ja, a, ua, l ) !*****************************************************************************80 ! !! ILU_CR computes the incomplete LU factorization of a matrix. ! ! Discussion: ! ! The matrix A is assumed to be stored in compressed row format. Only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA(I) through IA(I+1)-1. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 27 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(N+1), JA(NZ_NUM), the row and column ! indices of the matrix values. The row vector has been compressed. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input, integer ( kind = 4 ) UA(N), the index of the diagonal element ! of each row. ! ! Output, real ( kind = 8 ) L(NZ_NUM), the ILU factorization of A. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) iw(n) integer ( kind = 4 ) j integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) jj integer ( kind = 4 ) jrow integer ( kind = 4 ) jw integer ( kind = 4 ) k real ( kind = 8 ) l(nz_num) real ( kind = 8 ) tl integer ( kind = 4 ) ua(n) ! ! Copy A. ! l(1:nz_num) = a(1:nz_num) do i = 1, n ! ! IW points to the nonzero entries in row I. ! iw(1:n) = -1 do k = ia(i), ia(i+1) - 1 iw(ja(k)) = k end do do j = ia(i), ia(i+1) - 1 jrow = ja(j) if ( i <= jrow ) then exit end if tl = l(j) * l(ua(jrow)) l(j) = tl do jj = ua(jrow) + 1, ia(jrow+1) - 1 jw = iw(ja(jj)) if ( jw /= -1 ) then l(jw) = l(jw) - tl * l(jj) end if end do end do ua(i) = j if ( jrow /= i ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'ILU_CR - Fatal error!' write ( *, '(a)' ) ' JROW ~= I' write ( *, '(a,i8)' ) ' JROW = ', jrow write ( *, '(a,i8)' ) ' I = ', i stop end if if ( l(j) == 0.0D+00 ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'ILU_CR - Fatal error!' write ( *, '(a,i8)' ) ' Zero pivot on step I = ', i write ( *, '(a,i8,a)' ) ' L(', j, ') = 0.0' stop end if l(j) = 1.0D+00 / l(j) end do l(ua(1:n)) = 1.0D+00 / l(ua(1:n)) return end subroutine lus_cr ( n, nz_num, ia, ja, l, ua, r, z ) !*****************************************************************************80 ! !! LUS_CR applies the incomplete LU preconditioner. ! ! Discussion: ! ! The linear system M * Z = R is solved for Z. M is the incomplete ! LU preconditioner matrix, and R is a vector supplied by the user. ! So essentially, we're solving L * U * Z = R. ! ! The matrix A is assumed to be stored in compressed row format. Only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA(I) through IA(I+1)-1. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 18 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(N+1), JA(NZ_NUM), the row and column ! indices of the matrix values. The row vector has been compressed. ! ! Input, real ( kind = 8 ) L(NZ_NUM), the matrix values. ! ! Input, integer ( kind = 4 ) UA(N), the index of the diagonal element ! of each row. ! ! Input, real ( kind = 8 ) R(N), the right hand side. ! ! Output, real ( kind = 8 ) Z(N), the solution of the system M * Z = R. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) j integer ( kind = 4 ) ja(nz_num) real ( kind = 8 ) l(nz_num) real ( kind = 8 ) r(n) integer ( kind = 4 ) ua(n) real ( kind = 8 ) w(n) real ( kind = 8 ) z(n) ! ! Copy R in. ! w(1:n) = r(1:n) ! ! Solve L * w = w where L is unit lower triangular. ! do i = 2, n do j = ia(i), ua(i) - 1 w(i) = w(i) - l(j) * w(ja(j)) end do end do ! ! Solve U * w = w, where U is upper triangular. ! do i = n, 1, -1 do j = ua(i) + 1, ia(i+1) - 1 w(i) = w(i) - l(j) * w(ja(j)) end do w(i) = w(i) / l(ua(i)) end do ! ! Copy Z out. ! z(1:n) = w(1:n) return end subroutine mgmres_st ( n, nz_num, ia, ja, a, x, rhs, itr_max, mr, tol_abs, & tol_rel ) !*****************************************************************************80 ! !! MGMRES_ST applies restarted GMRES to a sparse triplet matrix. ! ! Discussion: ! ! The linear system A*X=B is solved iteratively. ! ! The matrix A is assumed to be stored in sparse triplet form. Only ! the nonzero entries of A are stored. For instance, the K-th nonzero ! entry in the matrix is stored by: ! ! A(K) = value of entry, ! IA(K) = row of entry, ! JA(K) = column of entry. ! ! Thanks to Jesus Pueblas Sanchez-Guerra for supplying two ! corrections to the code on 31 May 2007. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 13 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the linear system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzero matrix values. ! ! Input, integer ( kind = 4 ) IA(NZ_NUM), JA(NZ_NUM), the row and column ! indices of the matrix values. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input/output, real ( kind = 8 ) X(N); on input, an approximation to ! the solution. On output, an improved approximation. ! ! Input, real ( kind = 8 ) RHS(N), the right hand side of the linear system. ! ! Input, integer ( kind = 4 ) ITR_MAX, the maximum number of (outer) ! iterations to take. ! ! Input, integer ( kind = 4 ) MR, the maximum number of (inner) iterations ! to take. 0 < MR <= N. ! ! Input, real ( kind = 8 ) TOL_ABS, an absolute tolerance applied to the ! current residual. ! ! Input, real ( kind = 8 ) TOL_REL, a relative tolerance comparing the ! current residual to the initial residual. ! implicit none integer ( kind = 4 ) mr integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) real ( kind = 8 ) av real ( kind = 8 ) c(1:mr) real ( kind = 8 ), parameter :: delta = 1.0D-03 real ( kind = 8 ) g(1:mr+1) real ( kind = 8 ) h(1:mr+1,1:mr) real ( kind = 8 ) htmp integer ( kind = 4 ) i integer ( kind = 4 ) ia(nz_num) integer ( kind = 4 ) itr integer ( kind = 4 ) itr_max integer ( kind = 4 ) itr_used integer ( kind = 4 ) j integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k integer ( kind = 4 ) k_copy real ( kind = 8 ) mu real ( kind = 8 ) r(1:n) real ( kind = 8 ) rho real ( kind = 8 ) rho_tol real ( kind = 8 ) rhs(1:n) real ( kind = 8 ) s(1:mr) real ( kind = 8 ) tol_abs real ( kind = 8 ) tol_rel real ( kind = 8 ) v(1:n,1:mr+1) logical, parameter :: verbose = .true. real ( kind = 8 ) x(1:n) real ( kind = 8 ) y(1:mr+1) itr_used = 0 if ( n < mr ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'MGMRES_ST - Fatal error!' write ( *, '(a)' ) ' N < MR.' write ( *, '(a,i8)' ) ' N = ', n write ( *, '(a,i8)' ) ' MR = ', mr stop end if do itr = 1, itr_max call ax_st ( n, nz_num, ia, ja, a, x, r ) r(1:n) = rhs(1:n) - r(1:n) rho = sqrt ( dot_product ( r(1:n), r(1:n) ) ) if ( verbose ) then write ( *, '(a,i8,a,g14.6)' ) ' ITR = ', itr, ' Residual = ', rho end if if ( itr == 1 ) then rho_tol = rho * tol_rel end if v(1:n,1) = r(1:n) / rho g(1) = rho g(2:mr+1) = 0.0D+00 h(1:mr+1,1:mr) = 0.0D+00 do k = 1, mr k_copy = k call ax_st ( n, nz_num, ia, ja, a, v(1:n,k), v(1:n,k+1) ) av = sqrt ( dot_product ( v(1:n,k+1), v(1:n,k+1) ) ) do j = 1, k h(j,k) = dot_product ( v(1:n,k+1), v(1:n,j) ) v(1:n,k+1) = v(1:n,k+1) - h(j,k) * v(1:n,j) end do h(k+1,k) = sqrt ( dot_product ( v(1:n,k+1), v(1:n,k+1) ) ) if ( av + delta * h(k+1,k) == av ) then do j = 1, k htmp = dot_product ( v(1:n,k+1), v(1:n,j) ) h(j,k) = h(j,k) + htmp v(1:n,k+1) = v(1:n,k+1) - htmp * v(1:n,j) end do h(k+1,k) = sqrt ( dot_product ( v(1:n,k+1), v(1:n,k+1) ) ) end if if ( h(k+1,k) /= 0.0D+00 ) then v(1:n,k+1) = v(1:n,k+1) / h(k+1,k) end if if ( 1 < k ) then y(1:k+1) = h(1:k+1,k) do j = 1, k - 1 call mult_givens ( c(j), s(j), j, y(1:k+1) ) end do h(1:k+1,k) = y(1:k+1) end if mu = sqrt ( h(k,k)**2 + h(k+1,k)**2 ) c(k) = h(k,k) / mu s(k) = -h(k+1,k) / mu h(k,k) = c(k) * h(k,k) - s(k) * h(k+1,k) h(k+1,k) = 0.0D+00 call mult_givens ( c(k), s(k), k, g(1:k+1) ) rho = abs ( g(k+1) ) itr_used = itr_used + 1 if ( verbose ) then write ( *, '(a,i8,a,g14.6)' ) ' K = ', k, ' Residual = ', rho end if if ( rho <= rho_tol .and. rho <= tol_abs ) then exit end if end do k = k_copy - 1 y(k+1) = g(k+1) / h(k+1,k+1) do i = k, 1, -1 y(i) = ( g(i) - dot_product ( h(i,i+1:k+1), y(i+1:k+1) ) ) / h(i,i) end do do i = 1, n x(i) = x(i) + dot_product ( v(i,1:k+1), y(1:k+1) ) end do if ( rho <= rho_tol .and. rho <= tol_abs ) then exit end if end do if ( verbose ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'MGMRES_ST:' write ( *, '(a,i8)' ) ' Iterations = ', itr_used write ( *, '(a,g14.6)' ) ' Final residual = ', rho end if return end subroutine mult_givens ( c, s, k, g ) !*****************************************************************************80 ! !! MULT_GIVENS applies a Givens rotation to two successive entries of a vector. ! ! Discussion: ! ! In order to make it easier to compare this code with the Original C, ! the vector indexing is 0-based. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 08 August 2006 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, real ( kind = 8 ) C, S, the cosine and sine of a Givens ! rotation. ! ! Input, integer ( kind = 4 ) K, indicates the location of the first ! vector entry. ! ! Input/output, real ( kind = 8 ) G(1:K+1), the vector to be modified. ! On output, the Givens rotation has been applied to entries G(K) and G(K+1). ! implicit none integer ( kind = 4 ) k real ( kind = 8 ) c real ( kind = 8 ) g(1:k+1) real ( kind = 8 ) g1 real ( kind = 8 ) g2 real ( kind = 8 ) s g1 = c * g(k) - s * g(k+1) g2 = s * g(k) + c * g(k+1) g(k) = g1 g(k+1) = g2 return end subroutine pmgmres_ilu_cr ( n, nz_num, ia, ja, a, x, rhs, itr_max, mr, & tol_abs, tol_rel ) !*****************************************************************************80 ! !! PMGMRES_ILU_CR applies the preconditioned restarted GMRES algorithm. ! ! Discussion: ! ! The matrix A is assumed to be stored in compressed row format. Only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA(I) through IA(I+1)-1. ! ! This routine uses the incomplete LU decomposition for the ! preconditioning. This preconditioner requires that the sparse ! matrix data structure supplies a storage position for each diagonal ! element of the matrix A, and that each diagonal element of the ! matrix A is not zero. ! ! Thanks to Jesus Pueblas Sanchez-Guerra for supplying two ! corrections to the code on 31 May 2007. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 28 August 2012 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the linear system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzero matrix values. ! ! Input, integer ( kind = 4 ) IA(N+1), JA(NZ_NUM), the row and column indices ! of the matrix values. The row vector has been compressed. ! ! Input, real ( kind = 8 ) A(NZ_NUM), the matrix values. ! ! Input/output, real ( kind = 8 ) X(N); on input, an approximation to ! the solution. On output, an improved approximation. ! ! Input, real ( kind = 8 ) RHS(N), the right hand side of the linear system. ! ! Input, integer ( kind = 4 ) ITR_MAX, the maximum number of (outer) ! iterations to take. ! ! Input, integer ( kind = 4 ) MR, the maximum number of (inner) iterations ! to take. MR must be less than N. ! ! Input, real ( kind = 8 ) TOL_ABS, an absolute tolerance applied to the ! current residual. ! ! Input, real ( kind = 8 ) TOL_REL, a relative tolerance comparing the ! current residual to the initial residual. ! implicit none integer ( kind = 4 ) mr integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) real ( kind = 8 ) av real ( kind = 8 ) c(mr+1) real ( kind = 8 ), parameter :: delta = 1.0D-03 real ( kind = 8 ) g(mr+1) real ( kind = 8 ) h(mr+1,mr) real ( kind = 8 ) htmp integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) itr integer ( kind = 4 ) itr_max integer ( kind = 4 ) itr_used integer ( kind = 4 ) j integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k integer ( kind = 4 ) k_copy real ( kind = 8 ) l(ia(n+1)+1) real ( kind = 8 ) mu real ( kind = 8 ) r(n) real ( kind = 8 ) rho real ( kind = 8 ) rho_tol real ( kind = 8 ) rhs(n) real ( kind = 8 ) s(mr+1) real ( kind = 8 ) tol_abs real ( kind = 8 ) tol_rel integer ( kind = 4 ) ua(n) real ( kind = 8 ) v(n,mr+1); logical, parameter :: verbose = .true. real ( kind = 8 ) x(n) real ( kind = 8 ) y(mr+1) itr_used = 0 call rearrange_cr ( n, nz_num, ia, ja, a ) call diagonal_pointer_cr ( n, nz_num, ia, ja, ua ) call ilu_cr ( n, nz_num, ia, ja, a, ua, l ) if ( verbose ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'PMGMRES_ILU_CR' write ( *, '(a,i4)' ) ' Number of unknowns = ', n end if do itr = 1, itr_max call ax_cr ( n, nz_num, ia, ja, a, x, r ) r(1:n) = rhs(1:n) - r(1:n) call lus_cr ( n, nz_num, ia, ja, l, ua, r, r ) rho = sqrt ( dot_product ( r, r ) ) if ( verbose ) then write ( *, '(a,i4,a,g14.6)' ) ' ITR = ', itr, ' Residual = ', rho end if if ( itr == 1 ) then rho_tol = rho * tol_rel end if v(1:n,1) = r(1:n) / rho g(1) = rho g(2:mr+1) = 0.0D+00 h(1:mr+1,1:mr) = 0.0D+00 do k = 1, mr k_copy = k call ax_cr ( n, nz_num, ia, ja, a, v(1:n,k), v(1:n,k+1) ) call lus_cr ( n, nz_num, ia, ja, l, ua, v(1:n,k+1), v(1:n,k+1) ) av = sqrt ( dot_product ( v(1:n,k+1), v(1:n,k+1) ) ) do j = 1, k h(j,k) = dot_product ( v(1:n,k+1), v(1:n,j) ) v(1:n,k+1) = v(1:n,k+1) - v(1:n,j) * h(j,k) end do h(k+1,k) = sqrt ( dot_product ( v(1:n,k+1), v(1:n,k+1) ) ) if ( ( av + delta * h(k+1,k)) == av ) then do j = 1, k htmp = dot_product ( v(1:n,k+1), v(1:n,j) ) h(j,k) = h(j,k) + htmp v(1:n,k+1) = v(1:n,k+1) - htmp * v(1:n,j) end do h(k+1,k) = sqrt ( dot_product ( v(1:n,k+1), v(1:n,k+1) ) ) end if if ( h(k+1,k) /= 0.0D+00 ) then v(1:n,k+1) = v(1:n,k+1) / h(k+1,k) end if if ( 1 < k ) then y(1:k+1) = h(1:k+1,k) do j = 1, k - 1 call mult_givens ( c(j), s(j), j, y ) end do h(1:k+1,k) = y(1:k+1) end if mu = sqrt ( h(k,k)**2 + h(k+1,k)**2 ) c(k) = h(k,k) / mu s(k) = -h(k+1,k) / mu h(k,k) = c(k) * h(k,k) - s(k) * h(k+1,k) h(k+1,k) = 0.0D+00 call mult_givens ( c(k), s(k), k, g ) rho = abs ( g(k+1) ) itr_used = itr_used + 1 if ( verbose ) then write ( *, '(a,i4,a,g14.6)' ) ' K = ', k, ' Residual = ', rho end if if ( rho <= rho_tol .and. rho <= tol_abs ) then exit end if end do k = k_copy - 1 y(k+1) = g(k+1) / h(k+1,k+1) do i = k, 1, -1 y(i) = ( g(i) - dot_product ( h(i,i+1:k+1), y(i+1:k+1) ) ) / h(i,i) end do do i = 1, n x(i) = x(i) + dot_product ( v(i,1:k+1), y(1:k+1) ) end do if ( rho <= rho_tol .and. rho <= tol_abs ) then exit end if end do if ( verbose ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'PMGMRES_ILU_CR:' write ( *, '(a,i6)' ) ' Iterations = ', itr_used write ( *, '(a,g14.6)' ) ' Final residual = ', rho end if return end subroutine r8vec_uniform_01 ( n, seed, r ) !*****************************************************************************80 ! !! R8VEC_UNIFORM_01 returns a unit pseudorandom R8VEC. ! ! Discussion: ! ! An R8VEC is a vector of real ( kind = 8 ) values. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 05 July 2006 ! ! Author: ! ! John Burkardt ! ! Reference: ! ! Paul Bratley, Bennett Fox, Linus Schrage, ! A Guide to Simulation, ! Second Edition, ! Springer, 1987, ! ISBN: 0387964673, ! LC: QA76.9.C65.B73. ! ! Bennett Fox, ! Algorithm 647: ! Implementation and Relative Efficiency of Quasirandom ! Sequence Generators, ! ACM Transactions on Mathematical Software, ! Volume 12, Number 4, December 1986, pages 362-376. ! ! Pierre L'Ecuyer, ! Random Number Generation, ! in Handbook of Simulation, ! edited by Jerry Banks, ! Wiley, 1998, ! ISBN: 0471134031, ! LC: T57.62.H37. ! ! Peter Lewis, Allen Goodman, James Miller, ! A Pseudo-Random Number Generator for the System/360, ! IBM Systems Journal, ! Volume 8, Number 2, 1969, pages 136-143. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the number of entries in the vector. ! ! Input/output, integer ( kind = 4 ) SEED, the "seed" value, which ! should NOT be 0. On output, SEED has been updated. ! ! Output, real ( kind = 8 ) R(N), the vector of pseudorandom values. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) i integer ( kind = 4 ) k integer ( kind = 4 ) seed real ( kind = 8 ) r(n) if ( seed == 0 ) then write ( *, '(a)' ) ' ' write ( *, '(a)' ) 'R8VEC_UNIFORM_01 - Fatal error!' write ( *, '(a)' ) ' Input value of SEED = 0.' stop end if do i = 1, n k = seed / 127773 seed = 16807 * ( seed - k * 127773 ) - k * 2836 if ( seed < 0 ) then seed = seed + 2147483647 end if r(i) = real ( seed, kind = 8 ) * 4.656612875D-10 end do return end subroutine rearrange_cr ( n, nz_num, ia, ja, a ) !*****************************************************************************80 ! !! REARRANGE_CR sorts a sparse compressed row matrix. ! ! Discussion: ! ! This routine guarantees that the entries in the CR matrix ! are properly sorted. ! ! After the sorting, the entries of the matrix are rearranged in such ! a way that the entries of each column are listed in ascending order ! of their column values. ! ! The matrix A is assumed to be stored in compressed row format. Only ! the nonzero entries of A are stored. The vector JA stores the ! column index of the nonzero value. The nonzero values are sorted ! by row, and the compressed row vector IA then has the property that ! the entries in A and JA that correspond to row I occur in indices ! IA(I) through IA(I+1)-1. ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 17 July 2007 ! ! Author: ! ! Original C version by Lili Ju. ! FORTRAN90 version by John Burkardt. ! ! Reference: ! ! Richard Barrett, Michael Berry, Tony Chan, James Demmel, ! June Donato, Jack Dongarra, Victor Eijkhout, Roidan Pozo, ! Charles Romine, Henk van der Vorst, ! Templates for the Solution of Linear Systems: ! Building Blocks for Iterative Methods, ! SIAM, 1994. ! ISBN: 0898714710, ! LC: QA297.8.T45. ! ! Tim Kelley, ! Iterative Methods for Linear and Nonlinear Equations, ! SIAM, 2004, ! ISBN: 0898713528, ! LC: QA297.8.K45. ! ! Yousef Saad, ! Iterative Methods for Sparse Linear Systems, ! Second Edition, ! SIAM, 2003, ! ISBN: 0898715342, ! LC: QA188.S17. ! ! Parameters: ! ! Input, integer ( kind = 4 ) N, the order of the system. ! ! Input, integer ( kind = 4 ) NZ_NUM, the number of nonzeros. ! ! Input, integer ( kind = 4 ) IA(N+1), the compressed row indices. ! ! Input/output, integer ( kind = 4 ) JA(NZ_NUM), the column indices. ! On output, these may have been rearranged by the sorting. ! ! Input/output, real ( kind = 8 ) A(NZ_NUM), the matrix values. On output, ! the matrix values may have been moved somewhat because of the sorting. ! implicit none integer ( kind = 4 ) n integer ( kind = 4 ) nz_num real ( kind = 8 ) a(nz_num) integer ( kind = 4 ) i integer ( kind = 4 ) ia(n+1) integer ( kind = 4 ) i4temp integer ( kind = 4 ) ja(nz_num) integer ( kind = 4 ) k integer ( kind = 4 ) l real ( kind = 8 ) r8temp do i = 1, n do k = ia(i), ia(i+1) - 2 do l = k + 1, ia(i+1) - 1 if ( ja(l) < ja(k) ) then i4temp = ja(l) ja(l) = ja(k) ja(k) = i4temp r8temp = a(l) a(l) = a(k) a(k) = r8temp end if end do end do end do return end subroutine timestamp ( ) !*****************************************************************************80 ! !! TIMESTAMP prints the current YMDHMS date as a time stamp. ! ! Example: ! ! 31 May 2001 9:45:54.872 AM ! ! Licensing: ! ! This code is distributed under the GNU LGPL license. ! ! Modified: ! ! 18 May 2013 ! ! Author: ! ! John Burkardt ! ! Parameters: ! ! None ! implicit none character ( len = 8 ) ampm integer ( kind = 4 ) d integer ( kind = 4 ) h integer ( kind = 4 ) m integer ( kind = 4 ) mm character ( len = 9 ), parameter, dimension(12) :: month = (/ & 'January ', 'February ', 'March ', 'April ', & 'May ', 'June ', 'July ', 'August ', & 'September', 'October ', 'November ', 'December ' /) integer ( kind = 4 ) n integer ( kind = 4 ) s integer ( kind = 4 ) values(8) integer ( kind = 4 ) y call date_and_time ( values = values ) y = values(1) m = values(2) d = values(3) h = values(5) n = values(6) s = values(7) mm = values(8) if ( h < 12 ) then ampm = 'AM' else if ( h == 12 ) then if ( n == 0 .and. s == 0 ) then ampm = 'Noon' else ampm = 'PM' end if else h = h - 12 if ( h < 12 ) then ampm = 'PM' else if ( h == 12 ) then if ( n == 0 .and. s == 0 ) then ampm = 'Midnight' else ampm = 'AM' end if end if end if write ( *, '(i2.2,1x,a,1x,i4,2x,i2,a1,i2.2,a1,i2.2,a1,i3.3,1x,a)' ) & d, trim ( month(m) ), y, h, ':', n, ':', s, '.', mm, trim ( ampm ) return end