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288 lines
11 KiB
Fortran
288 lines
11 KiB
Fortran
!!$
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!!$
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!!$ MLD2P4 version 1.1
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!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
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!!$ based on PSBLAS (Parallel Sparse BLAS version 2.3.1)
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!!$
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!!$ (C) Copyright 2008,2009
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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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! File: mld_dilu_bld.f90
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!
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! Subroutine: mld_dilu_bld
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! Version: real
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!
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! This routine computes an incomplete LU (ILU) factorization of the diagonal
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! blocks of a distributed matrix. This factorization is used to build the
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! 'base preconditioner' (block-Jacobi preconditioner/solver, Additive Schwarz
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! preconditioner) corresponding to a certain level of a multilevel preconditioner.
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!
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! The following factorizations are available:
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! - ILU(k), i.e. ILU factorization with fill-in level k,
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! - MILU(k), i.e. modified ILU factorization with fill-in level k,
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! - ILU(k,t), i.e. ILU with threshold (i.e. drop tolerance) t and k additional
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! entries in each row of the L and U factors with respect to the initial
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! sparsity pattern.
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! Note that the meaning of k in ILU(k,t) is different from that in ILU(k) and
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! MILU(k).
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!
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! For details on the above factorizations see
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! Y. Saad, Iterative Methods for Sparse Linear Systems, Second Edition,
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! SIAM, 2003, Chapter 10.
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!
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! Note that that this routine handles the ILU(0) factorization separately,
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! through mld_ilu0_fact, for performance reasons.
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!
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!
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! Arguments:
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! a - type(psb_dspmat_type), input.
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! The sparse matrix structure containing the local matrix.
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! Note that if p%iprcparm(mld_sub_ovr_) > 0, i.e. the
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! 'base' Additive Schwarz preconditioner has overlap greater than
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! 0, and p%iprcparm(mld_sub_ren_) = 0, i.e. a reordering of the
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! matrix has not been performed (see mld_fact_bld), then a contains
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! only the 'original' local part of the distributed matrix,
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! i.e. the rows of the matrix held by the calling process according
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! to the initial data distribution.
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! p - type(mld_dbaseprec_type), input/output.
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! The 'base preconditioner' data structure. In input, p%iprcparm
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! contains information on the type of factorization to be computed.
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! In output, p%av(mld_l_pr_) and p%av(mld_u_pr_) contain the
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! incomplete L and U factors (without their diagonals), and p%d
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! contains the diagonal of the incomplete U factor. For more
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! details on p see its description in mld_prec_type.f90.
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! info - integer, output.
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! Error code.
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! blck - type(psb_dspmat_type), input, optional.
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! The sparse matrix structure containing the remote rows of the
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! distributed matrix, that have been retrieved by mld_as_bld
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! to build an Additive Schwarz base preconditioner with overlap
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! greater than 0. If the overlap is 0 or the matrix has been reordered
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! (see mld_fact_bld), then blck does not contain any row.
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!
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subroutine mld_dilu_bld(a,p,upd,info,blck)
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use psb_sparse_mod
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use mld_inner_mod, mld_protect_name => mld_dilu_bld
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implicit none
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! Arguments
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type(psb_d_sparse_mat), intent(in), target :: a
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type(mld_dbaseprec_type), intent(inout) :: p
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character, intent(in) :: upd
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integer, intent(out) :: info
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type(psb_d_sparse_mat), intent(in), optional :: blck
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! Local Variables
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integer :: i, nztota, err_act, n_row, nrow_a
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character :: trans, unitd
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integer :: debug_level, debug_unit
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integer :: ictxt,np,me
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character(len=20) :: name, ch_err
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if(psb_get_errstatus().ne.0) return
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info=psb_success_
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name='mld_dilu_bld'
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call psb_erractionsave(err_act)
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debug_unit = psb_get_debug_unit()
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debug_level = psb_get_debug_level()
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ictxt = psb_cd_get_context(p%desc_data)
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call psb_info(ictxt, me, np)
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if (debug_level >= psb_debug_outer_) &
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& write(debug_unit,*) me,' ',trim(name),' start'
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trans = 'N'
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unitd = 'U'
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n_row = psb_cd_get_local_rows(p%desc_data)
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if (psb_toupper(upd) == 'F') then
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!
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! Check the memory available to hold the incomplete L and U factors
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! and allocate it if needed
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!
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if (allocated(p%av)) then
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if (size(p%av) < mld_bp_ilu_avsz_) then
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do i=1, size(p%av)
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call p%av(i)%free()
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enddo
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deallocate(p%av,stat=info)
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endif
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end if
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if (.not.allocated(p%av)) then
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allocate(p%av(mld_max_avsz_),stat=info)
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if (info /= psb_success_) then
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call psb_errpush(psb_err_alloc_dealloc_,name)
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goto 9999
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end if
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endif
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nrow_a = a%get_nrows()
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nztota = a%get_nzeros()
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if (present(blck)) then
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nztota = nztota + blck%get_nzeros()
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end if
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call p%av(mld_l_pr_)%csall(n_row,n_row,info,nztota)
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if (info == psb_success_) call p%av(mld_u_pr_)%csall(n_row,n_row,info,nztota)
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if(info /= psb_success_) then
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info=psb_err_from_subroutine_
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ch_err='psb_sp_all'
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call psb_errpush(info,name,a_err=ch_err)
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goto 9999
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end if
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if (allocated(p%d)) then
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if (size(p%d) < n_row) then
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deallocate(p%d)
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endif
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endif
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if (.not.allocated(p%d)) then
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allocate(p%d(n_row),stat=info)
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if (info /= psb_success_) then
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call psb_errpush(psb_err_from_subroutine_,name,a_err='Allocate')
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goto 9999
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end if
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endif
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select case(p%iprcparm(mld_sub_solve_))
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case (mld_ilu_t_)
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!
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! ILU(k,t)
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!
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select case(p%iprcparm(mld_sub_fillin_))
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case(:-1)
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! Error: fill-in <= -1
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call psb_errpush(psb_err_input_value_invalid_i_,name,i_err=(/3,p%iprcparm(mld_sub_fillin_),0,0,0/))
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goto 9999
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case(0:)
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! Fill-in >= 0
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call mld_ilut_fact(p%iprcparm(mld_sub_fillin_),p%rprcparm(mld_sub_iluthrs_),&
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& a, p%av(mld_l_pr_),p%av(mld_u_pr_),p%d,info,blck=blck)
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end select
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if(info /= psb_success_) then
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info=psb_err_from_subroutine_
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ch_err='mld_ilut_fact'
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call psb_errpush(info,name,a_err=ch_err)
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goto 9999
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end if
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case(mld_ilu_n_,mld_milu_n_)
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!
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! ILU(k) and MILU(k)
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!
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select case(p%iprcparm(mld_sub_fillin_))
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case(:-1)
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! Error: fill-in <= -1
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call psb_errpush(psb_err_input_value_invalid_i_,name,i_err=(/3,p%iprcparm(mld_sub_fillin_),0,0,0/))
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goto 9999
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case(0)
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! Fill-in 0
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! Separate implementation of ILU(0) for better performance.
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! There seems to be a problem with the separate implementation of MILU(0),
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! contained into mld_ilu0_fact. This must be investigated. For the time being,
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! resort to the implementation of MILU(k) with k=0.
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if (p%iprcparm(mld_sub_solve_) == mld_ilu_n_) then
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call mld_ilu0_fact(p%iprcparm(mld_sub_solve_),a,p%av(mld_l_pr_),p%av(mld_u_pr_),&
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& p%d,info,blck=blck,upd=upd)
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else
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call mld_iluk_fact(p%iprcparm(mld_sub_fillin_),p%iprcparm(mld_sub_solve_),&
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& a,p%av(mld_l_pr_),p%av(mld_u_pr_),p%d,info,blck=blck)
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endif
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case(1:)
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! Fill-in >= 1
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! The same routine implements both ILU(k) and MILU(k)
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call mld_iluk_fact(p%iprcparm(mld_sub_fillin_),p%iprcparm(mld_sub_solve_),&
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& a,p%av(mld_l_pr_),p%av(mld_u_pr_),p%d,info,blck=blck)
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end select
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if (info /= psb_success_) then
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info=psb_err_from_subroutine_
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ch_err='mld_iluk_fact'
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call psb_errpush(info,name,a_err=ch_err)
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goto 9999
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end if
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case default
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! If we end up here, something was wrong up in the call chain.
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call psb_errpush(psb_err_alloc_dealloc_,name)
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goto 9999
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end select
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else
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! Here we should add checks for reuse of L and U.
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! For the time being just throw an error.
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info = 31
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call psb_errpush(info, name, i_err=(/3,0,0,0,0/),a_err=upd)
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goto 9999
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!
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! What is an update of a factorization??
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! A first attempt could be to reuse EXACTLY the existing indices
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! as if it was an ILU(0) (since, effectively, the sparsity pattern
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! should not grow beyond what is already there).
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!
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call mld_ilu0_fact(p%iprcparm(mld_sub_solve_),a,&
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& p%av(mld_l_pr_),p%av(mld_u_pr_),&
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& p%d,info,blck=blck,upd=upd)
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end if
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call p%av(mld_l_pr_)%set_asb()
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call p%av(mld_l_pr_)%trim()
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call p%av(mld_u_pr_)%set_asb()
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call p%av(mld_u_pr_)%trim()
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if (debug_level >= psb_debug_outer_) &
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& write(debug_unit,*) me,' ',trim(name),' end'
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call psb_erractionrestore(err_act)
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return
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9999 continue
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call psb_erractionrestore(err_act)
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if (err_act.eq.psb_act_abort_) then
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call psb_error()
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return
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end if
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return
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end subroutine mld_dilu_bld
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