!!$ !!$ !!$ MLD2P4 version 2.0 !!$ MultiLevel Domain Decomposition Parallel Preconditioners Package !!$ based on PSBLAS (Parallel Sparse BLAS version 3.3) !!$ !!$ (C) Copyright 2008, 2010, 2012, 2015 !!$ !!$ Salvatore Filippone University of Rome Tor Vergata !!$ Alfredo Buttari CNRS-IRIT, Toulouse !!$ Pasqua D'Ambra ICAR-CNR, Naples !!$ Daniela di Serafino Second University of Naples !!$ !!$ Redistribution and use in source and binary forms, with or without !!$ modification, are permitted provided that the following conditions !!$ are met: !!$ 1. Redistributions of source code must retain the above copyright !!$ notice, this list of conditions and the following disclaimer. !!$ 2. Redistributions in binary form must reproduce the above copyright !!$ notice, this list of conditions, and the following disclaimer in the !!$ documentation and/or other materials provided with the distribution. !!$ 3. The name of the MLD2P4 group or the names of its contributors may !!$ not be used to endorse or promote products derived from this !!$ software without specific written permission. !!$ !!$ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS !!$ ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED !!$ TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR !!$ PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE MLD2P4 GROUP OR ITS CONTRIBUTORS !!$ BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR !!$ CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF !!$ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS !!$ INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN !!$ CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) !!$ ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE !!$ POSSIBILITY OF SUCH DAMAGE. !!$ !!$ subroutine mld_d_jac_smoother_apply(alpha,sm,x,beta,y,desc_data,& & trans,sweeps,work,info,init,initu) use psb_base_mod use mld_d_jac_smoother, mld_protect_name => mld_d_jac_smoother_apply implicit none type(psb_desc_type), intent(in) :: desc_data class(mld_d_jac_smoother_type), intent(inout) :: sm real(psb_dpk_),intent(inout) :: x(:) real(psb_dpk_),intent(inout) :: y(:) real(psb_dpk_),intent(in) :: alpha,beta character(len=1),intent(in) :: trans integer(psb_ipk_), intent(in) :: sweeps real(psb_dpk_),target, intent(inout) :: work(:) integer(psb_ipk_), intent(out) :: info character, intent(in), optional :: init real(psb_dpk_),intent(inout), optional :: initu(:) integer(psb_ipk_) :: n_row,n_col real(psb_dpk_), allocatable :: tx(:),ty(:) real(psb_dpk_), pointer :: ww(:), aux(:) integer(psb_ipk_) :: ictxt,np,me,i, err_act character :: trans_, init_ character(len=20) :: name='d_jac_smoother_apply' call psb_erractionsave(err_act) info = psb_success_ if (present(init)) then init_ = psb_toupper(init) else init_='Z' end if trans_ = psb_toupper(trans) select case(trans_) case('N') case('T','C') case default call psb_errpush(psb_err_iarg_invalid_i_,name) goto 9999 end select if (.not.allocated(sm%sv)) then info = 1121 call psb_errpush(info,name) goto 9999 end if n_row = desc_data%get_local_rows() n_col = desc_data%get_local_cols() if (n_col <= size(work)) then ww => work(1:n_col) if ((4*n_col+n_col) <= size(work)) then aux => work(n_col+1:) else allocate(aux(4*n_col),stat=info) if (info /= psb_success_) then info=psb_err_alloc_request_ call psb_errpush(info,name,& & i_err=(/4*n_col,izero,izero,izero,izero/),& & a_err='real(psb_dpk_)') goto 9999 end if endif else allocate(ww(n_col),aux(4*n_col),stat=info) if (info /= psb_success_) then info=psb_err_alloc_request_ call psb_errpush(info,name,& & i_err=(/5*n_col,izero,izero,izero,izero/),& & a_err='real(psb_dpk_)') goto 9999 end if endif if (sweeps == 0) then ! ! K^0 = I ! zero sweeps of any smoother is just the identity. ! call psb_geaxpby(alpha,x,beta,y,desc_data,info) else if ((.not.sm%sv%is_iterative()).and.((sweeps == 1).or.(sm%nnz_nd_tot==0))) then ! if .not.sv%is_iterative, there's no need to pass init call sm%sv%apply(alpha,x,beta,y,desc_data,trans_,aux,info) if (info /= psb_success_) then call psb_errpush(psb_err_internal_error_,& & name,a_err='Error in sub_aply Jacobi Sweeps = 1') goto 9999 endif else if (sweeps >= 1) then ! ! ! Apply multiple sweeps of a block-Jacobi solver ! to compute an approximate solution of a linear system. ! ! call psb_geasb(tx,desc_data,info) call psb_geasb(ty,desc_data,info) select case (init_) case('Z') tx(:) = dzero case('Y') call psb_geaxpby(done,y,dzero,tx,desc_data,info) case('U') if (.not.present(initu)) then call psb_errpush(psb_err_internal_error_,name,& & a_err='missing initu to smoother_apply') goto 9999 end if call psb_geaxpby(done,initu,dzero,tx,desc_data,info) case default call psb_errpush(psb_err_internal_error_,name,& & a_err='wrong init to smoother_apply') goto 9999 end select do i=1, sweeps ! ! Compute Y(j+1) = D^(-1)*(X-ND*Y(j)), where D and ND are the ! block diagonal part and the remaining part of the local matrix ! and Y(j) is the approximate solution at sweep j. ! call psb_geaxpby(done,x,dzero,ty,desc_data,info) call psb_spmm(-done,sm%nd,tx,done,ty,desc_data,info,work=aux,trans=trans_) if (info /= psb_success_) exit call sm%sv%apply(done,ty,dzero,tx,desc_data,trans_,aux,info,init='Y') if (info /= psb_success_) exit end do if (info == psb_success_) call psb_geaxpby(alpha,tx,beta,y,desc_data,info) if (info /= psb_success_) then info=psb_err_internal_error_ call psb_errpush(info,name,& & a_err='subsolve with Jacobi sweeps > 1') goto 9999 end if deallocate(tx,ty,stat=info) if (info /= psb_success_) then info=psb_err_internal_error_ call psb_errpush(info,name,& & a_err='final cleanup with Jacobi sweeps > 1') goto 9999 end if else info = psb_err_iarg_neg_ call psb_errpush(info,name,& & i_err=(/itwo,sweeps,izero,izero,izero/)) goto 9999 endif if (n_col <= size(work)) then if ((4*n_col+n_col) <= size(work)) then else deallocate(aux) endif else deallocate(ww,aux) endif call psb_erractionrestore(err_act) return 9999 call psb_error_handler(err_act) return end subroutine mld_d_jac_smoother_apply