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amg4psblas/mlprec/mld_dsub_aply.f90

297 lines
10 KiB
Fortran

!!$
!!$
!!$ MLD2P4 version 1.0
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS version 2.2)
!!$
!!$ (C) Copyright 2008
!!$
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$ Alfredo Buttari University of Rome Tor Vergata
!!$ 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.
!!$
!!$
! File mld_dsub_aply.f90
!
! Subroutine: mld_dsub_aply
! Version: real
!
! This routine computes
!
! Y = beta*Y + alpha*op(K^(-1))*X,
!
! where
! - K is a suitable matrix, as specified below,
! - op(K^(-1)) is K^(-1) or its transpose, according to the value of the
! argument trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
! Depending on K, alpha and beta (and on the communication descriptor desc_data
! - see the arguments below), the above computation may correspond to one of
! the following tasks:
!
! 1. Application of a block-Jacobi preconditioner associated to a matrix A
! distributed among the processes. Here K is the preconditioner, op(K^(-1))
! = K^(-1), alpha = 1 and beta = 0.
!
! 2. Application of block-Jacobi sweeps to compute an approximate solution of
! a linear system
! A*Y = X,
!
! distributed among the processes (note that a single block-Jacobi sweep,
! with null starting guess, corresponds to the application of a block-Jacobi
! preconditioner). Here K^(-1) denotes the iteration matrix of the
! block-Jacobi solver, op(K^(-1)) = K^(-1), alpha = 1 and beta = 0.
!
! 3. Solution, through the LU factorization, of a linear system
!
! A*Y = X,
!
! distributed among the processes. Here K = L*U = A, op(K^(-1)) = K^(-1),
! alpha = 1 and beta = 0.
!
! 4. (Approximate) solution, through the LU or incomplete LU factorization, of
! a linear system
! A*Y = X,
!
! replicated on the processes. Here K = L*U = A or K = L*U ~ A, op(K^(-1)) =
! K^(-1), alpha = 1 and beta = 0.
!
! The block-Jacobi preconditioner or solver and the L and U factors of the LU
! or ILU factorizations have been built by the routine mld_fact_bld and stored
! into the 'base preconditioner' data structure prec. See mld_fact_bld for more
! details.
!
! This routine is used by mld_as_aply, to apply a 'base' block-Jacobi or
! Additive Schwarz (AS) preconditioner at any level of a multilevel preconditioner,
! or a block-Jacobi or LU or ILU solver at the coarsest level of a multilevel
! preconditioner.
!
! Tasks 1, 3 and 4 may be selected when prec%iprcparm(mld_smoother_sweeps_) = 1,
! while task 2 is selected when prec%iprcparm(mld_smoother_sweeps_) > 1. Furthermore
! Tasks 1, 2 and 3 may be performed when the matrix A is
! distributed among the processes (prec%iprcparm(mld_coarse_mat_) = mld_distr_mat_),
! while task 4 may be performed when A is replicated on the processes
! (prec%iprcparm(mld_coarse_mat_) = mld_repl_mat_). Note that the matrix A is
! distributed among the processes at each level of the multilevel preconditioner,
! except the coarsest one, where it may be either distributed or replicated on
! the processes. Tasks 2, 3 and 4 are performed only at the coarsest level.
! Note also that this routine manages implicitly the fact that
! the matrix is distributed or replicated, i.e. it does not make any explicit
! reference to the value of prec%iprcparm(mld_coarse_mat_).
!
! Arguments:
!
! alpha - real(psb_dpk_), input.
! The scalar alpha.
! prec - type(mld_dbaseprec_type), input.
! The 'base preconditioner' data structure containing the local
! part of the preconditioner or solver.
! x - real(psb_dpk_), dimension(:), input.
! The local part of the vector X.
! beta - real(psb_dpk_), input.
! The scalar beta.
! y - real(psb_dpk_), dimension(:), input/output.
! The local part of the vector Y.
! desc_data - type(psb_desc_type), input.
! The communication descriptor associated to the matrix to be
! preconditioned or 'inverted'.
! trans - character(len=1), input.
! If trans='N','n' then op(K^(-1)) = K^(-1);
! if trans='T','t' then op(K^(-1)) = K^(-T) (transpose of K^(-1)).
! If prec%iprcparm(mld_smoother_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - real(psb_dpk_), dimension (:), target.
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
! info - integer, output.
! Error code.
!
subroutine mld_dsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_inner_mod, mld_protect_name => mld_dsub_aply
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
mld2p4 Changelog krylov/psb_prec_mod.F90 mlprec/mld_cas_aply.f90 mlprec/mld_cas_bld.f90 mlprec/mld_cbaseprec_aply.f90 mlprec/mld_cbaseprec_bld.f90 mlprec/mld_cdiag_bld.f90 mlprec/mld_cfact_bld.f90 mlprec/mld_cilu_bld.f90 mlprec/mld_cmlprec_aply.f90 mlprec/mld_cprecbld.f90 mlprec/mld_cslu_bld.f90 mlprec/mld_cslud_bld.f90 mlprec/mld_csp_renum.f90 mlprec/mld_csub_aply.f90 mlprec/mld_csub_solve.f90 mlprec/mld_cumf_bld.f90 mlprec/mld_das_aply.f90 mlprec/mld_das_bld.f90 mlprec/mld_dbaseprec_aply.f90 mlprec/mld_dbaseprec_bld.f90 mlprec/mld_ddiag_bld.f90 mlprec/mld_dfact_bld.f90 mlprec/mld_dilu_bld.f90 mlprec/mld_dmlprec_aply.f90 mlprec/mld_dprecbld.f90 mlprec/mld_dslu_bld.f90 mlprec/mld_dslud_bld.f90 mlprec/mld_dsp_renum.f90 mlprec/mld_dsub_aply.f90 mlprec/mld_dsub_solve.f90 mlprec/mld_dumf_bld.f90 mlprec/mld_inner_mod.f90 mlprec/mld_move_alloc_mod.F90 mlprec/mld_prec_type.f90 mlprec/mld_sas_aply.f90 mlprec/mld_sas_bld.f90 mlprec/mld_sbaseprec_aply.f90 mlprec/mld_sbaseprec_bld.f90 mlprec/mld_sdiag_bld.f90 mlprec/mld_sfact_bld.f90 mlprec/mld_silu_bld.f90 mlprec/mld_smlprec_aply.f90 mlprec/mld_sprecbld.f90 mlprec/mld_sslu_bld.f90 mlprec/mld_sslud_bld.f90 mlprec/mld_ssp_renum.f90 mlprec/mld_ssub_aply.f90 mlprec/mld_ssub_solve.f90 mlprec/mld_sumf_bld.f90 mlprec/mld_zas_aply.f90 mlprec/mld_zas_bld.f90 mlprec/mld_zbaseprec_aply.f90 mlprec/mld_zbaseprec_bld.f90 mlprec/mld_zdiag_bld.f90 mlprec/mld_zfact_bld.f90 mlprec/mld_zilu_bld.f90 mlprec/mld_zmlprec_aply.f90 mlprec/mld_zprecbld.f90 mlprec/mld_zslu_bld.f90 mlprec/mld_zslud_bld.f90 mlprec/mld_zsp_renum.f90 mlprec/mld_zsub_aply.f90 mlprec/mld_zsub_solve.f90 mlprec/mld_zumf_bld.f90 Changed names from XbaseprcY to XbaseprecY.
16 years ago
type(mld_dbaseprec_type), intent(in) :: prec
real(psb_dpk_),intent(in) :: x(:)
real(psb_dpk_),intent(inout) :: y(:)
real(psb_dpk_),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
real(psb_dpk_),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
real(psb_dpk_), pointer :: ww(:), aux(:), tx(:),ty(:)
integer :: ictxt,np,me,i, err_act
character(len=20) :: name
character :: trans_
name='mld_dsub_aply'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = psb_toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
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 /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='real(psb_dpk_)')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='real(psb_dpk_)')
goto 9999
end if
endif
if (prec%iprcparm(mld_smoother_sweeps_) == 1) then
call mld_sub_solve(alpha,prec,x,beta,y,desc_data,trans_,aux,info)
if (info /= 0) then
call psb_errpush(4001,name,a_err='Error in sub_aply Jacobi Sweeps = 1')
goto 9999
endif
else if (prec%iprcparm(mld_smoother_sweeps_) > 1) then
!
!
! Apply prec%iprcparm(mld_smoother_sweeps_) sweeps of a block-Jacobi solver
! to compute an approximate solution of a linear system.
!
!
if (size(prec%av) < mld_ap_nd_) then
info = 4011
goto 9999
endif
allocate(tx(n_col),ty(n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
& a_err='real(psb_dpk_)')
goto 9999
end if
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smoother_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.
!
ty(1:n_row) = x(1:n_row)
call psb_spmm(-done,prec%av(mld_ap_nd_),tx,done,ty,&
& prec%desc_data,info,work=aux,trans=trans_)
if (info /=0) exit
call mld_sub_solve(done,prec,ty,dzero,tx,desc_data,trans_,aux,info)
if (info /=0) exit
end do
if (info == 0) call psb_geaxpby(alpha,tx,beta,y,desc_data,info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='subsolve with Jacobi sweeps > 1')
goto 9999
end if
deallocate(tx,ty,stat=info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='final cleanup with Jacobi sweeps > 1')
goto 9999
end if
else
info = 10
call psb_errpush(info,name,&
& i_err=(/2,prec%iprcparm(mld_smoother_sweeps_),0,0,0/))
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 continue
call psb_erractionrestore(err_act)
if (err_act.eq.psb_act_abort_) then
call psb_error()
return
end if
return
end subroutine mld_dsub_aply