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amg4psblas/mlprec/impl/smoother/mld_s_jac_smoother_apply_ve...

194 lines
6.3 KiB
Fortran

!!$
!!$
!!$ 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_s_jac_smoother_apply_vect(alpha,sm,x,beta,y,desc_data,trans,&
& sweeps,work,info)
use psb_base_mod
use mld_s_jac_smoother, mld_protect_name => mld_s_jac_smoother_apply_vect
implicit none
type(psb_desc_type), intent(in) :: desc_data
class(mld_s_jac_smoother_type), intent(inout) :: sm
type(psb_s_vect_type),intent(inout) :: x
type(psb_s_vect_type),intent(inout) :: y
real(psb_spk_),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
integer(psb_ipk_), intent(in) :: sweeps
real(psb_spk_),target, intent(inout) :: work(:)
integer(psb_ipk_), intent(out) :: info
integer(psb_ipk_) :: n_row,n_col
type(psb_s_vect_type) :: tx, ty
real(psb_spk_), pointer :: ww(:), aux(:)
integer(psb_ipk_) :: ictxt,np,me,i, err_act
character :: trans_
character(len=20) :: name='s_jac_smoother_apply'
call psb_erractionsave(err_act)
info = psb_success_
trans_ = psb_toupper(trans)
select case(trans_)
case('N')
case('T')
case('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_spk_)')
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_spk_)')
goto 9999
end if
endif
!!$ write(0,*) 'Jacobi smoother with ',sweeps
if ((.not.sm%sv%is_iterative()).and.((sweeps == 1).or.(sm%nnz_nd_tot==0))) then
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 tx%bld(x%get_nrows(),mold=x%v)
call tx%set(szero)
call ty%bld(x%get_nrows(),mold=x%v)
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(sone,x,szero,ty,desc_data,info)
call psb_spmm(-sone,sm%nd,tx,sone,ty,desc_data,info,work=aux,trans=trans_)
if (info /= psb_success_) exit
call sm%sv%apply(sone,ty,szero,tx,desc_data,trans_,aux,info)
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
call tx%free(info)
if (info == psb_success_) call ty%free(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_s_jac_smoother_apply_vect