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216 lines
7.3 KiB
Fortran
216 lines
7.3 KiB
Fortran
!
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!
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! MLD2P4 version 2.1
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! MultiLevel Domain Decomposition Parallel Preconditioners Package
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! based on PSBLAS (Parallel Sparse BLAS version 3.4)
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!
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! (C) Copyright 2008, 2010, 2012, 2015, 2017
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!
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! Salvatore Filippone Cranfield University
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! Ambra Abdullahi Hassan University of Rome Tor Vergata
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! Alfredo Buttari CNRS-IRIT, Toulouse
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! Pasqua D'Ambra ICAR-CNR, Naples
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! Daniela di Serafino University of Campania "L. Vanvitelli", Caserta
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!
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! Redistribution and use in source and binary forms, with or without
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! modification, are permitted provided that the following conditions
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! are met:
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! 1. Redistributions of source code must retain the above copyright
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! notice, this list of conditions and the following disclaimer.
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! 2. Redistributions in binary form must reproduce the above copyright
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! notice, this list of conditions, and the following disclaimer in the
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! documentation and/or other materials provided with the distribution.
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! 3. The name of the MLD2P4 group or the names of its contributors may
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! not be used to endorse or promote products derived from this
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! software without specific written permission.
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!
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! THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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! ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
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! TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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! PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE MLD2P4 GROUP OR ITS CONTRIBUTORS
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! BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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! CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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! SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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! INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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! CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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! ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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! POSSIBILITY OF SUCH DAMAGE.
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!
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!
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subroutine mld_c_jac_smoother_apply_vect(alpha,sm,x,beta,y,desc_data,trans,&
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& sweeps,work,info,init,initu)
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use psb_base_mod
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use mld_c_jac_smoother, mld_protect_name => mld_c_jac_smoother_apply_vect
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implicit none
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type(psb_desc_type), intent(in) :: desc_data
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class(mld_c_jac_smoother_type), intent(inout) :: sm
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type(psb_c_vect_type),intent(inout) :: x
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type(psb_c_vect_type),intent(inout) :: y
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complex(psb_spk_),intent(in) :: alpha,beta
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character(len=1),intent(in) :: trans
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integer(psb_ipk_), intent(in) :: sweeps
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complex(psb_spk_),target, intent(inout) :: work(:)
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integer(psb_ipk_), intent(out) :: info
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character, intent(in), optional :: init
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type(psb_c_vect_type),intent(inout), optional :: initu
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integer(psb_ipk_) :: n_row,n_col
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type(psb_c_vect_type) :: tx, ty
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complex(psb_spk_), pointer :: aux(:)
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integer(psb_ipk_) :: ictxt,np,me,i, err_act
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character :: trans_, init_
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character(len=20) :: name='c_jac_smoother_apply_v'
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call psb_erractionsave(err_act)
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info = psb_success_
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if (present(init)) then
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init_ = psb_toupper(init)
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else
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init_='Z'
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end if
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trans_ = psb_toupper(trans)
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select case(trans_)
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case('N')
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case('T','C')
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case default
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call psb_errpush(psb_err_iarg_invalid_i_,name)
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goto 9999
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end select
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if (.not.allocated(sm%sv)) then
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info = 1121
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call psb_errpush(info,name)
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goto 9999
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end if
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n_row = desc_data%get_local_rows()
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n_col = desc_data%get_local_cols()
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if (4*n_col <= size(work)) then
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aux => work(:)
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else
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allocate(aux(4*n_col),stat=info)
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if (info /= psb_success_) then
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info=psb_err_alloc_request_
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call psb_errpush(info,name,&
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& i_err=(/4*n_col,izero,izero,izero,izero/),&
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& a_err='complex(psb_spk_)')
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goto 9999
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end if
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endif
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if ((.not.sm%sv%is_iterative()).and.((sweeps == 1).or.(sm%nnz_nd_tot==0))) then
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! if .not.sv%is_iterative, there's no need to pass init
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call sm%sv%apply(alpha,x,beta,y,desc_data,trans_,aux,info)
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if (info /= psb_success_) then
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call psb_errpush(psb_err_internal_error_,&
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& name,a_err='Error in sub_aply Jacobi Sweeps = 1')
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goto 9999
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endif
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else if (sweeps >= 0) then
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!
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!
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! Apply multiple sweeps of a block-Jacobi solver
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! to compute an approximate solution of a linear system.
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!
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!
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call psb_geasb(tx,desc_data,info,mold=x%v,scratch=.true.)
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call psb_geasb(ty,desc_data,info,mold=x%v,scratch=.true.)
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!
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! Unroll the first iteration and fold it inside SELECT CASE
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! this will save one AXPBY and one SPMM when INIT=Z, and will be
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! significant when sweeps=1 (a common case)
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!
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select case (init_)
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case('Z')
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call sm%sv%apply(cone,x,czero,ty,desc_data,trans_,aux,info,init='Z')
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case('Y')
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call psb_geaxpby(cone,x,czero,tx,desc_data,info)
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call psb_geaxpby(cone,y,czero,ty,desc_data,info)
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call psb_spmm(-cone,sm%nd,ty,cone,tx,desc_data,info,work=aux,trans=trans_)
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call sm%sv%apply(cone,tx,czero,ty,desc_data,trans_,aux,info,init='Y')
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case('U')
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if (.not.present(initu)) then
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call psb_errpush(psb_err_internal_error_,name,&
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& a_err='missing initu to smoother_apply')
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goto 9999
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end if
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call psb_geaxpby(cone,x,czero,tx,desc_data,info)
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call psb_geaxpby(cone,initu,czero,ty,desc_data,info)
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call psb_spmm(-cone,sm%nd,ty,cone,tx,desc_data,info,work=aux,trans=trans_)
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call sm%sv%apply(cone,tx,czero,ty,desc_data,trans_,aux,info,init='Y')
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case default
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call psb_errpush(psb_err_internal_error_,name,&
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& a_err='wrong init to smoother_apply')
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goto 9999
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end select
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do i=1, sweeps-1
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!
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! Compute Y(j+1) = D^(-1)*(X-ND*Y(j)), where D and ND are the
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! block diagonal part and the remaining part of the local matrix
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! and Y(j) is the approximate solution at sweep j.
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!
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call psb_geaxpby(cone,x,czero,tx,desc_data,info)
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call psb_spmm(-cone,sm%nd,ty,cone,tx,desc_data,info,work=aux,trans=trans_)
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if (info /= psb_success_) exit
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call sm%sv%apply(cone,tx,czero,ty,desc_data,trans_,aux,info,init='Y')
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if (info /= psb_success_) exit
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end do
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if (info == psb_success_) call psb_geaxpby(alpha,ty,beta,y,desc_data,info)
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if (info /= psb_success_) then
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info=psb_err_internal_error_
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call psb_errpush(info,name,&
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& a_err='subsolve with Jacobi sweeps > 1')
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goto 9999
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end if
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call tx%free(info)
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if (info == psb_success_) call ty%free(info)
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if (info /= psb_success_) then
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info=psb_err_internal_error_
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call psb_errpush(info,name,&
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& a_err='final cleanup with Jacobi sweeps > 1')
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goto 9999
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end if
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else
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info = psb_err_iarg_neg_
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call psb_errpush(info,name,&
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& i_err=(/itwo,sweeps,izero,izero,izero/))
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goto 9999
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endif
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if (.not.(4*n_col <= size(work))) then
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deallocate(aux)
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endif
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call psb_erractionrestore(err_act)
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return
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9999 call psb_error_handler(err_act)
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return
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end subroutine mld_c_jac_smoother_apply_vect
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