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193 lines
6.2 KiB
Fortran
193 lines
6.2 KiB
Fortran
!!$
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!!$
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!!$ MLD2P4 version 2.0
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!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
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!!$ based on PSBLAS (Parallel Sparse BLAS version 3.3)
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!!$
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!!$ (C) Copyright 2008, 2010, 2012, 2015
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!!$
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!!$ Salvatore Filippone 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 Second University of Naples
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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_d_jac_smoother_apply_vect(alpha,sm,x,beta,y,desc_data,trans,&
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& sweeps,work,info)
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use psb_base_mod
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use mld_d_jac_smoother, mld_protect_name => mld_d_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_d_jac_smoother_type), intent(inout) :: sm
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type(psb_d_vect_type),intent(inout) :: x
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type(psb_d_vect_type),intent(inout) :: y
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real(psb_dpk_),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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real(psb_dpk_),target, intent(inout) :: work(:)
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integer(psb_ipk_), intent(out) :: info
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integer(psb_ipk_) :: n_row,n_col
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type(psb_d_vect_type) :: tx, ty
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real(psb_dpk_), pointer :: ww(:), aux(:)
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integer(psb_ipk_) :: ictxt,np,me,i, err_act
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character :: trans_
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character(len=20) :: name='d_jac_smoother_apply'
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call psb_erractionsave(err_act)
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info = psb_success_
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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')
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case('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 (n_col <= size(work)) then
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ww => work(1:n_col)
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if ((4*n_col+n_col) <= size(work)) then
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aux => work(n_col+1:)
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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='real(psb_dpk_)')
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goto 9999
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end if
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endif
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else
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allocate(ww(n_col),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=(/5*n_col,izero,izero,izero,izero/),&
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& a_err='real(psb_dpk_)')
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goto 9999
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end if
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endif
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if ((sweeps == 1).or.(sm%nnz_nd_tot==0)) then
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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 > 1) 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 tx%bld(x%get_nrows(),mold=x%v)
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call tx%set(dzero)
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call ty%bld(x%get_nrows(),mold=x%v)
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do i=1, sweeps
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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(done,x,dzero,ty,desc_data,info)
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call psb_spmm(-done,sm%nd,tx,done,ty,desc_data,info,work=aux,trans=trans_)
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if (info /= psb_success_) exit
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call sm%sv%apply(done,ty,dzero,tx,desc_data,trans_,aux,info)
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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,tx,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 (n_col <= size(work)) then
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if ((4*n_col+n_col) <= size(work)) then
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else
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deallocate(aux)
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endif
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else
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deallocate(ww,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_d_jac_smoother_apply_vect
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