mld2p4-2:
mlprec/Makefile mlprec/mld_csub_aply.f90 mlprec/mld_csub_solve.f90 mlprec/mld_dsub_aply.f90 mlprec/mld_dsub_solve.f90 mlprec/mld_inner_mod.f90 mlprec/mld_ssub_aply.f90 mlprec/mld_ssub_solve.f90 mlprec/mld_zsub_aply.f90 mlprec/mld_zsub_solve.f90 These are no longer needed.stopcriterion
Salvatore Filippone
14 years ago
parent
a60b38628d
commit
def7d9c65c
@ -1,296 +0,0 @@
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!!$
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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 3.0)
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!!$
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!!$ (C) Copyright 2008,2009,2010
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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_csub_aply.f90
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!
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! Subroutine: mld_csub_aply
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! Version: complex
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!
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! This routine computes
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!
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! Y = beta*Y + alpha*op(K^(-1))*X,
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!
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! where
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! - K is a suitable matrix, as specified below,
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! - op(K^(-1)) is K^(-1) or its transpose, according to the value of the
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! argument trans,
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! - X and Y are vectors,
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! - alpha and beta are scalars.
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!
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! Depending on K, alpha and beta (and on the communication descriptor desc_data
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! - see the arguments below), the above computation may correspond to one of
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! the following tasks:
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!
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! 1. Application of a block-Jacobi preconditioner associated to a matrix A
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! distributed among the processes. Here K is the preconditioner, op(K^(-1))
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! = K^(-1), alpha = 1 and beta = 0.
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!
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! 2. Application of block-Jacobi sweeps to compute an approximate solution of
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! a linear system
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! A*Y = X,
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!
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! distributed among the processes (note that a single block-Jacobi sweep,
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! with null starting guess, corresponds to the application of a block-Jacobi
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! preconditioner). Here K^(-1) denotes the iteration matrix of the
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! block-Jacobi solver, op(K^(-1)) = K^(-1), alpha = 1 and beta = 0.
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!
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! 3. Solution, through the LU factorization, of a linear system
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!
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! A*Y = X,
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!
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! distributed among the processes. Here K = L*U = A, op(K^(-1)) = K^(-1),
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! alpha = 1 and beta = 0.
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!
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! 4. (Approximate) solution, through the LU or incomplete LU factorization, of
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! a linear system
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! A*Y = X,
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!
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! replicated on the processes. Here K = L*U = A or K = L*U ~ A, op(K^(-1)) =
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! K^(-1), alpha = 1 and beta = 0.
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!
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! The block-Jacobi preconditioner or solver and the L and U factors of the LU
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! or ILU factorizations have been built by the routine mld_fact_bld and stored
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! into the 'base preconditioner' data structure prec. See mld_fact_bld for more
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! details.
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!
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! This routine is used by mld_as_aply, to apply a 'base' block-Jacobi or
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! Additive Schwarz (AS) preconditioner at any level of a multilevel preconditioner,
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! or a block-Jacobi or LU or ILU solver at the coarsest level of a multilevel
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! preconditioner.
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!
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! Tasks 1, 3 and 4 may be selected when prec%iprcparm(mld_smoother_sweeps_) = 1,
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! while task 2 is selected when prec%iprcparm(mld_smoother_sweeps_) > 1.
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! Furthermore, tasks 1, 2 and 3 may be performed when the matrix A is distributed
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! among the processes (p%precv(ilev)%iprcparm(mld_coarse_mat_) = mld_distr_mat_,
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! where p%precv(ilev) is the one-level data structure associated to the level
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! ilev at which mld_sub_aply is called), while task 4 may be performed when A
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! is replicated on the processes (p%precv(ilev)%iprcparm(mld_coarse_mat_) =
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! mld_repl_mat_). Note that the matrix A is distributed among the processes
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! at each level of the multilevel preconditioner, except the coarsest one, where
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! it may be either distributed or replicated on the processes. Tasks 2, 3 and 4
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! are performed only at the coarsest level. Note also that this routine manages
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! implicitly the fact that the matrix is distributed or replicated, i.e. it does not
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! make any explicit reference to the value of p%precv(ilev)%iprcparm(mld_coarse_mat_).
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!
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! Arguments:
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!
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! alpha - complex(psb_spk_), input.
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! The scalar alpha.
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! prec - type(mld_cbaseprec_type), input.
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! The 'base preconditioner' data structure containing the local
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! part of the preconditioner or solver.
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! x - complex(psb_spk_), dimension(:), input.
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! The local part of the vector X.
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! beta - complex(psb_spk_), input.
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! The scalar beta.
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! y - complex(psb_spk_), dimension(:), input/output.
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! The local part of the vector Y.
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! desc_data - type(psb_desc_type), input.
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! The communication descriptor associated to the matrix to be
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! preconditioned or 'inverted'.
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! trans - character(len=1), input.
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! If trans='N','n' then op(K^(-1)) = K^(-1);
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! if trans='T','t' then op(K^(-1)) = K^(-T) (transpose of K^(-1)).
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! if trans='C','c' then op(K^(-1)) = K^(-C) (transpose conjugate of K^(-1)).
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! If prec%iprcparm(mld_smoother_sweeps_) > 1, the value of trans provided
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! in input is ignored.
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! work - complex(psb_spk_), dimension (:), target.
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! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
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! info - integer, output.
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! Error code.
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!
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subroutine mld_csub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
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use psb_sparse_mod
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use mld_inner_mod, mld_protect_name => mld_csub_aply
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implicit none
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! Arguments
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type(psb_desc_type), intent(in) :: desc_data
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type(mld_cbaseprec_type), intent(in) :: prec
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complex(psb_spk_),intent(in) :: x(:)
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complex(psb_spk_),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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complex(psb_spk_),target, intent(inout) :: work(:)
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integer, intent(out) :: info
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! Local variables
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integer :: n_row,n_col
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complex(psb_spk_), pointer :: ww(:), aux(:), tx(:),ty(:)
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integer :: ictxt,np,me,i, err_act
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character(len=20) :: name
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character :: trans_
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name='mld_csub_aply'
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info = psb_success_
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call psb_erractionsave(err_act)
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ictxt=psb_cd_get_context(desc_data)
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call psb_info(ictxt, me, np)
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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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n_row = psb_cd_get_local_rows(desc_data)
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n_col = psb_cd_get_local_cols(desc_data)
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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,i_err=(/4*n_col,0,0,0,0/),&
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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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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,i_err=(/5*n_col,0,0,0,0/),&
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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 (prec%iprcparm(mld_smoother_sweeps_) == 1) then
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call mld_sub_solve(alpha,prec,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_,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 (prec%iprcparm(mld_smoother_sweeps_) > 1) then
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!
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!
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! Apply prec%iprcparm(mld_smoother_sweeps_) 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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if (size(prec%av) < mld_ap_nd_) then
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info = psb_err_from_subroutine_non_
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goto 9999
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endif
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allocate(tx(n_col),ty(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,i_err=(/2*n_col,0,0,0,0/),&
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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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tx = czero
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ty = czero
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do i=1, prec%iprcparm(mld_smoother_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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ty(1:n_row) = x(1:n_row)
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call psb_spmm(-cone,prec%av(mld_ap_nd_),tx,cone,ty,&
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& prec%desc_data,info,work=aux,trans=trans_)
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if (info /= psb_success_) exit
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call mld_sub_solve(cone,prec,ty,czero,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,a_err='subsolve with Jacobi sweeps > 1')
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goto 9999
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end if
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deallocate(tx,ty,stat=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,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=(/2,prec%iprcparm(mld_smoother_sweeps_),0,0,0/))
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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 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_csub_aply
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@ -1,324 +0,0 @@
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!!$
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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 3.0)
|
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!!$
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!!$ (C) Copyright 2008,2009,2010
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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
|
||||
!!$ 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.
|
||||
!!$
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!!$
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! File mld_csub_solve.f90
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!
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! Subroutine: mld_csub_solve
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! Version: complex
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!
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! This routine computes
|
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!
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! Y = beta*Y + alpha*op(K^(-1))*X,
|
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!
|
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! where
|
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! - K is a factored matrix, as specified below,
|
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! - op(K^(-1)) is K^(-1) or its transpose, according to the value of the
|
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! argument trans,
|
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! - X and Y are vectors,
|
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! - alpha and beta are scalars.
|
||||
!
|
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! 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
|
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! the following tasks:
|
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!
|
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! 1. approximate solution of a linear system
|
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!
|
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! A*Y = X,
|
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!
|
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! by using the L and U factors computed with an ILU factorization of A.
|
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! In this case K = L*U ~ A, alpha = 1 and beta = 0. The factors L and U
|
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! (and the matrix A) are either distributed and block-diagonal or replicated.
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!
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! 2. Solution of a linear system
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!
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! A*Y = X,
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!
|
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! by using the L and U factors computed with a LU factorization of A. In this
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! case K = L*U = A, alpha = 1 and beta = 0. The LU factorization is performed
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! by one of the following auxiliary pakages:
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! a. UMFPACK,
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! b. SuperLU,
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! c. SuperLU_Dist.
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! In the cases a. and b., the factors L and U (and the matrix A) are either
|
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! distributed and block diagonal) or replicated; in the case c., L, U (and A)
|
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! are distributed.
|
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!
|
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! This routine is used by mld_dsub_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
|
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! preconditioner.
|
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!
|
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!
|
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! Arguments:
|
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!
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! alpha - complex(psb_spk_), input.
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! The scalar alpha.
|
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! prec - type(mld_cbaseprec_type), input.
|
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! The 'base preconditioner' data structure containing the local
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! part of the L and U factors of the matrix A.
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! x - complex(psb_spk_), dimension(:), input.
|
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! The local part of the vector X.
|
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! beta - complex(psb_spk_), input.
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! The scalar beta.
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! y - complex(psb_spk_), dimension(:), input/output.
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! The local part of the vector Y.
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! desc_data - type(psb_desc_type), input.
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! The communication descriptor associated to the matrix to be
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! preconditioned or 'inverted'.
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! trans - character(len=1), input.
|
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! If trans='N','n' then op(K^(-1)) = K^(-1);
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! if trans='T','t' then op(K^(-1)) = K^(-T) (transpose of K^(-1)).
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! if trans='C','c' then op(K^(-1)) = K^(-C) (transpose conjugate of K^(-1)).
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! If prec%iprcparm(mld_smoother_sweeps_) > 1, the value of trans provided
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! in input is ignored.
|
||||
! work - complex(psb_spk_), dimension (:), target.
|
||||
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
|
||||
! info - integer, output.
|
||||
! Error code.
|
||||
!
|
||||
subroutine mld_csub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
|
||||
|
||||
use psb_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_csub_solve
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
type(mld_cbaseprec_type), intent(in) :: prec
|
||||
complex(psb_spk_),intent(in) :: x(:)
|
||||
complex(psb_spk_),intent(inout) :: y(:)
|
||||
complex(psb_spk_),intent(in) :: alpha,beta
|
||||
character(len=1), intent(in) :: trans
|
||||
complex(psb_spk_),target, intent(inout) :: work(:)
|
||||
integer, intent(out) :: info
|
||||
|
||||
! Local variables
|
||||
integer :: n_row,n_col
|
||||
complex(psb_spk_), pointer :: ww(:), aux(:), tx(:),ty(:)
|
||||
integer :: ictxt,np,me,i, err_act
|
||||
character(len=20) :: name
|
||||
character :: trans_
|
||||
|
||||
interface
|
||||
subroutine mld_cumf_solve(flag,m,x,b,n,ptr,info)
|
||||
use psb_sparse_mod
|
||||
integer, intent(in) :: flag,m,n,ptr
|
||||
integer, intent(out) :: info
|
||||
complex(psb_spk_), intent(in) :: b(*)
|
||||
complex(psb_spk_), intent(inout) :: x(*)
|
||||
end subroutine mld_cumf_solve
|
||||
end interface
|
||||
|
||||
name='mld_csub_solve'
|
||||
info = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
|
||||
& a_err='complex(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,0,0,0,0/),&
|
||||
& a_err='complex(psb_spk_)')
|
||||
goto 9999
|
||||
end if
|
||||
endif
|
||||
|
||||
|
||||
select case(prec%iprcparm(mld_sub_solve_))
|
||||
case(mld_ilu_n_,mld_milu_n_,mld_ilu_t_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with ILU(k)/MILU(k)/ILU(k,t)
|
||||
! factorization of the blocks (distributed matrix) or approximately
|
||||
! solve a system through ILU(k)/MILU(k)/ILU(k,t) (replicated matrix).
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
|
||||
call psb_spsm(cone,prec%av(mld_l_pr_),x,czero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
|
||||
if (info == psb_success_) call psb_spsm(alpha,prec%av(mld_u_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_, work=aux)
|
||||
|
||||
case('T')
|
||||
call psb_spsm(cone,prec%av(mld_u_pr_),x,czero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_, work=aux)
|
||||
if(info == psb_success_) call psb_spsm(alpha,prec%av(mld_l_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_,work=aux)
|
||||
|
||||
case('C')
|
||||
call psb_spsm(cone,prec%av(mld_u_pr_),x,czero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=conjg(prec%d),choice=psb_none_, work=aux)
|
||||
if(info == psb_success_) call psb_spsm(alpha,prec%av(mld_l_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_,work=aux)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in ILU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
case(mld_slu_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The SuperLU package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_cslu_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case('T')
|
||||
call mld_cslu_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case('C')
|
||||
call mld_cslu_solve(2,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case(mld_sludist_)
|
||||
!
|
||||
! Solve a distributed linear system with the LU factorization.
|
||||
! The SuperLU_DIST package is used.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_csludist_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case('T')
|
||||
call mld_csludist_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case('C')
|
||||
call mld_csludist_solve(2,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLUDist subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case (mld_umf_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The UMFPACK package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_cumf_solve(0,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case('T')
|
||||
call mld_cumf_solve(1,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case('C')
|
||||
call mld_cumf_solve(2,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in UMF subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid mld_sub_solve_')
|
||||
goto 9999
|
||||
|
||||
end select
|
||||
|
||||
if (info /= psb_success_) then
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Error in subsolve ')
|
||||
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_csub_solve
|
||||
@ -1,296 +0,0 @@
|
||||
!!$
|
||||
!!$
|
||||
!!$ MLD2P4 version 2.0
|
||||
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
!!$ based on PSBLAS (Parallel Sparse BLAS version 3.0)
|
||||
!!$
|
||||
!!$ (C) Copyright 2008,2009,2010
|
||||
!!$
|
||||
!!$ 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.
|
||||
!!$
|
||||
!!$
|
||||
! 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 (p%precv(ilev)%iprcparm(mld_coarse_mat_) = mld_distr_mat_,
|
||||
! where p%precv(ilev) is the one-level data structure associated to the level
|
||||
! ilev at which mld_sub_aply is called), while task 4 may be performed when A
|
||||
! is replicated on the processes (p%precv(ilev)%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 p%precv(ilev)%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_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_dsub_aply
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
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 = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
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 /= 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 (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 = psb_err_from_subroutine_non_
|
||||
goto 9999
|
||||
endif
|
||||
|
||||
allocate(tx(n_col),ty(n_col),stat=info)
|
||||
if (info /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
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 /= psb_success_) exit
|
||||
|
||||
call mld_sub_solve(done,prec,ty,dzero,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
|
||||
|
||||
deallocate(tx,ty,stat=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=(/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
|
||||
@ -1,312 +0,0 @@
|
||||
!!$
|
||||
!!$
|
||||
!!$ MLD2P4 version 2.0
|
||||
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
!!$ based on PSBLAS (Parallel Sparse BLAS version 3.0)
|
||||
!!$
|
||||
!!$ (C) Copyright 2008,2009,2010
|
||||
!!$
|
||||
!!$ 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.
|
||||
!!$
|
||||
!!$
|
||||
! File mld_dsub_solve.f90
|
||||
!
|
||||
! Subroutine: mld_dsub_solve
|
||||
! Version: real
|
||||
!
|
||||
! This routine computes
|
||||
!
|
||||
! Y = beta*Y + alpha*op(K^(-1))*X,
|
||||
!
|
||||
! where
|
||||
! - K is a factored 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. approximate solution of a linear system
|
||||
!
|
||||
! A*Y = X,
|
||||
!
|
||||
! by using the L and U factors computed with an ILU factorization of A.
|
||||
! In this case K = L*U ~ A, alpha = 1 and beta = 0. The factors L and U
|
||||
! (and the matrix A) are either distributed and block-diagonal or replicated.
|
||||
!
|
||||
! 2. Solution of a linear system
|
||||
!
|
||||
! A*Y = X,
|
||||
!
|
||||
! by using the L and U factors computed with a LU factorization of A. In this
|
||||
! case K = L*U = A, alpha = 1 and beta = 0. The LU factorization is performed
|
||||
! by one of the following auxiliary pakages:
|
||||
! a. UMFPACK,
|
||||
! b. SuperLU,
|
||||
! c. SuperLU_Dist.
|
||||
! In the cases a. and b., the factors L and U (and the matrix A) are either
|
||||
! distributed and block diagonal) or replicated; in the case c., L, U (and A)
|
||||
! are distributed.
|
||||
!
|
||||
! This routine is used by mld_dsub_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.
|
||||
!
|
||||
!
|
||||
! 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 L and U factors of the matrix A.
|
||||
! 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_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
|
||||
|
||||
use psb_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_dsub_solve
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
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_
|
||||
|
||||
interface
|
||||
subroutine mld_dumf_solve(flag,m,x,b,n,ptr,info)
|
||||
use psb_sparse_mod
|
||||
integer, intent(in) :: flag,m,n,ptr
|
||||
integer, intent(out) :: info
|
||||
real(psb_dpk_), intent(in) :: b(*)
|
||||
real(psb_dpk_), intent(inout) :: x(*)
|
||||
end subroutine mld_dumf_solve
|
||||
end interface
|
||||
|
||||
name='mld_dsub_solve'
|
||||
info = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
|
||||
& a_err='real(psb_dpk_)')
|
||||
goto 9999
|
||||
end if
|
||||
endif
|
||||
|
||||
|
||||
select case(prec%iprcparm(mld_sub_solve_))
|
||||
case(mld_ilu_n_,mld_milu_n_,mld_ilu_t_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with ILU(k)/MILU(k)/ILU(k,t)
|
||||
! factorization of the blocks (distributed matrix) or approximately
|
||||
! solve a system through ILU(k)/MILU(k)/ILU(k,t) (replicated matrix).
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call psb_spsm(done,prec%av(mld_l_pr_),x,dzero,ww,desc_data,info,&
|
||||
& trans=trans_,scale='L',diag=prec%d,choice=psb_none_,work=aux)
|
||||
|
||||
if (info == psb_success_) call psb_spsm(alpha,prec%av(mld_u_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,scale='U',choice=psb_none_, work=aux)
|
||||
|
||||
case('T','C')
|
||||
call psb_spsm(done,prec%av(mld_u_pr_),x,dzero,ww,desc_data,info,&
|
||||
& trans=trans_,scale='L',diag=prec%d,choice=psb_none_,work=aux)
|
||||
if (info == psb_success_) call psb_spsm(alpha,prec%av(mld_l_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,scale='U',choice=psb_none_,work=aux)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in ILU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
case(mld_slu_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The SuperLU package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_dslu_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case('T','C')
|
||||
call mld_dslu_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case(mld_sludist_)
|
||||
!
|
||||
! Solve a distributed linear system with the LU factorization.
|
||||
! The SuperLU_DIST package is used.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_dsludist_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case('T','C')
|
||||
call mld_dsludist_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLUDist subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case (mld_umf_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The UMFPACK package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_dumf_solve(0,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case('T','C')
|
||||
call mld_dumf_solve(1,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in UMF subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid mld_sub_solve_')
|
||||
goto 9999
|
||||
|
||||
end select
|
||||
|
||||
if (info /= psb_success_) then
|
||||
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Error in subsolve')
|
||||
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_solve
|
||||
@ -1,297 +0,0 @@
|
||||
!!$
|
||||
!!$
|
||||
!!$ MLD2P4 version 2.0
|
||||
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
!!$ based on PSBLAS (Parallel Sparse BLAS version 3.0)
|
||||
!!$
|
||||
!!$ (C) Copyright 2008,2009,2010
|
||||
!!$
|
||||
!!$ 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.
|
||||
!!$
|
||||
!!$
|
||||
! File mld_ssub_aply.f90
|
||||
!
|
||||
! Subroutine: mld_ssub_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 (p%precv(ilev)%iprcparm(mld_coarse_mat_) = mld_distr_mat_,
|
||||
! where p%precv(ilev) is the one-level data structure associated to the level
|
||||
! ilev at which mld_sub_aply is called), while task 4 may be performed when A
|
||||
! is replicated on the processes (p%precv(ilev)%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 p%precv(ilev)%iprcparm(mld_coarse_mat_).
|
||||
!
|
||||
! Arguments:
|
||||
!
|
||||
! alpha - real(psb_spk_), input.
|
||||
! The scalar alpha.
|
||||
! prec - type(mld_sbaseprec_type), input.
|
||||
! The 'base preconditioner' data structure containing the local
|
||||
! part of the preconditioner or solver.
|
||||
! x - real(psb_spk_), dimension(:), input.
|
||||
! The local part of the vector X.
|
||||
! beta - real(psb_spk_), input.
|
||||
! The scalar beta.
|
||||
! y - real(psb_spk_), 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_spk_), dimension (:), target.
|
||||
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
|
||||
! info - integer, output.
|
||||
! Error code.
|
||||
!
|
||||
subroutine mld_ssub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
|
||||
|
||||
use psb_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_ssub_aply
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
type(mld_sbaseprec_type), intent(in) :: prec
|
||||
real(psb_spk_),intent(in) :: x(:)
|
||||
real(psb_spk_),intent(inout) :: y(:)
|
||||
real(psb_spk_),intent(in) :: alpha,beta
|
||||
character(len=1),intent(in) :: trans
|
||||
real(psb_spk_),target, intent(inout) :: work(:)
|
||||
integer, intent(out) :: info
|
||||
|
||||
! Local variables
|
||||
integer :: n_row,n_col
|
||||
real(psb_spk_), pointer :: ww(:), aux(:), tx(:),ty(:)
|
||||
integer :: ictxt,np,me,i, err_act
|
||||
character(len=20) :: name
|
||||
character :: trans_
|
||||
|
||||
name='mld_ssub_aply'
|
||||
info = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
|
||||
& 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,0,0,0,0/),&
|
||||
& a_err='real(psb_spk_)')
|
||||
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 /= 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 (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 = psb_err_from_subroutine_non_
|
||||
goto 9999
|
||||
endif
|
||||
|
||||
allocate(tx(n_col),ty(n_col),stat=info)
|
||||
if (info /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
|
||||
& a_err='real(psb_spk_)')
|
||||
goto 9999
|
||||
end if
|
||||
|
||||
tx = szero
|
||||
ty = szero
|
||||
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(-sone,prec%av(mld_ap_nd_),tx,sone,ty,&
|
||||
& prec%desc_data,info,work=aux,trans=trans_)
|
||||
|
||||
if (info /= psb_success_) exit
|
||||
|
||||
call mld_sub_solve(sone,prec,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
|
||||
|
||||
deallocate(tx,ty,stat=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=(/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_ssub_aply
|
||||
|
||||
@ -1,312 +0,0 @@
|
||||
!!$
|
||||
!!$
|
||||
!!$ MLD2P4 version 2.0
|
||||
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
!!$ based on PSBLAS (Parallel Sparse BLAS version 3.0)
|
||||
!!$
|
||||
!!$ (C) Copyright 2008,2009,2010
|
||||
!!$
|
||||
!!$ 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.
|
||||
!!$
|
||||
!!$
|
||||
! File mld_ssub_solve.f90
|
||||
!
|
||||
! Subroutine: mld_ssub_solve
|
||||
! Version: real
|
||||
!
|
||||
! This routine computes
|
||||
!
|
||||
! Y = beta*Y + alpha*op(K^(-1))*X,
|
||||
!
|
||||
! where
|
||||
! - K is a factored 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. approximate solution of a linear system
|
||||
!
|
||||
! A*Y = X,
|
||||
!
|
||||
! by using the L and U factors computed with an ILU factorization of A.
|
||||
! In this case K = L*U ~ A, alpha = 1 and beta = 0. The factors L and U
|
||||
! (and the matrix A) are either distributed and block-diagonal or replicated.
|
||||
!
|
||||
! 2. Solution of a linear system
|
||||
!
|
||||
! A*Y = X,
|
||||
!
|
||||
! by using the L and U factors computed with a LU factorization of A. In this
|
||||
! case K = L*U = A, alpha = 1 and beta = 0. The LU factorization is performed
|
||||
! by one of the following auxiliary pakages:
|
||||
! a. UMFPACK,
|
||||
! b. SuperLU,
|
||||
! c. SuperLU_Dist.
|
||||
! In the cases a. and b., the factors L and U (and the matrix A) are either
|
||||
! distributed and block diagonal) or replicated; in the case c., L, U (and A)
|
||||
! are distributed.
|
||||
!
|
||||
! This routine is used by mld_ssub_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.
|
||||
!
|
||||
!
|
||||
! Arguments:
|
||||
!
|
||||
! alpha - real(psb_spk_), input.
|
||||
! The scalar alpha.
|
||||
! prec - type(mld_sbaseprec_type), input.
|
||||
! The 'base preconditioner' data structure containing the local
|
||||
! part of the L and U factors of the matrix A.
|
||||
! x - real(psb_spk_), dimension(:), input.
|
||||
! The local part of the vector X.
|
||||
! beta - real(psb_spk_), input.
|
||||
! The scalar beta.
|
||||
! y - real(psb_spk_), 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_spk_), dimension (:), target.
|
||||
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
|
||||
! info - integer, output.
|
||||
! Error code.
|
||||
!
|
||||
subroutine mld_ssub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
|
||||
|
||||
use psb_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_ssub_solve
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
type(mld_sbaseprec_type), intent(in) :: prec
|
||||
real(psb_spk_),intent(in) :: x(:)
|
||||
real(psb_spk_),intent(inout) :: y(:)
|
||||
real(psb_spk_),intent(in) :: alpha,beta
|
||||
character(len=1),intent(in) :: trans
|
||||
real(psb_spk_),target, intent(inout) :: work(:)
|
||||
integer, intent(out) :: info
|
||||
|
||||
! Local variables
|
||||
integer :: n_row,n_col
|
||||
real(psb_spk_), pointer :: ww(:), aux(:), tx(:),ty(:)
|
||||
integer :: ictxt,np,me,i, err_act
|
||||
character(len=20) :: name
|
||||
character :: trans_
|
||||
|
||||
interface
|
||||
subroutine mld_sumf_solve(flag,m,x,b,n,ptr,info)
|
||||
use psb_sparse_mod
|
||||
integer, intent(in) :: flag,m,n,ptr
|
||||
integer, intent(out) :: info
|
||||
real(psb_spk_), intent(in) :: b(*)
|
||||
real(psb_spk_), intent(inout) :: x(*)
|
||||
end subroutine mld_sumf_solve
|
||||
end interface
|
||||
|
||||
name='mld_ssub_solve'
|
||||
info = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
|
||||
& 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,0,0,0,0/),&
|
||||
& a_err='real(psb_spk_)')
|
||||
goto 9999
|
||||
end if
|
||||
endif
|
||||
|
||||
|
||||
select case(prec%iprcparm(mld_sub_solve_))
|
||||
case(mld_ilu_n_,mld_milu_n_,mld_ilu_t_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with ILU(k)/MILU(k)/ILU(k,t)
|
||||
! factorization of the blocks (distributed matrix) or approximately
|
||||
! solve a system through ILU(k)/MILU(k)/ILU(k,t) (replicated matrix).
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
|
||||
call psb_spsm(sone,prec%av(mld_l_pr_),x,szero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
|
||||
if (info == psb_success_) call psb_spsm(alpha,prec%av(mld_u_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_, work=aux)
|
||||
|
||||
case('T','C')
|
||||
call psb_spsm(sone,prec%av(mld_u_pr_),x,szero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
|
||||
if (info == psb_success_) call psb_spsm(alpha,prec%av(mld_l_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_,work=aux)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in ILU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
case(mld_slu_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The SuperLU package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_sslu_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case('T','C')
|
||||
call mld_sslu_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case(mld_sludist_)
|
||||
!
|
||||
! Solve a distributed linear system with the LU factorization.
|
||||
! The SuperLU_DIST package is used.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_ssludist_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case('T','C')
|
||||
call mld_ssludist_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLUDist subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case (mld_umf_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The UMFPACK package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_sumf_solve(0,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case('T','C')
|
||||
call mld_sumf_solve(1,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in UMF subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid mld_sub_solve_')
|
||||
goto 9999
|
||||
|
||||
end select
|
||||
|
||||
if (info /= psb_success_) then
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Error in subsolve')
|
||||
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_ssub_solve
|
||||
|
||||
@ -1,297 +0,0 @@
|
||||
!!$
|
||||
!!$
|
||||
!!$ MLD2P4 version 2.0
|
||||
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
!!$ based on PSBLAS (Parallel Sparse BLAS version 3.0)
|
||||
!!$
|
||||
!!$ (C) Copyright 2008,2009,2010
|
||||
!!$
|
||||
!!$ 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.
|
||||
!!$
|
||||
!!$
|
||||
! File mld_zsub_aply.f90
|
||||
!
|
||||
! Subroutine: mld_zsub_aply
|
||||
! Version: complex
|
||||
!
|
||||
! 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 (p%precv(ilev)%iprcparm(mld_coarse_mat_) = mld_distr_mat_,
|
||||
! where p%precv(ilev) is the one-level data structure associated to the level
|
||||
! ilev at which mld_sub_aply is called), while task 4 may be performed when A
|
||||
! is replicated on the processes (p%precv(ilev)%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 p%precv(ilev)%iprcparm(mld_coarse_mat_).
|
||||
!
|
||||
! Arguments:
|
||||
!
|
||||
! alpha - complex(psb_dpk_), input.
|
||||
! The scalar alpha.
|
||||
! prec - type(mld_zbaseprec_type), input.
|
||||
! The 'base preconditioner' data structure containing the local
|
||||
! part of the preconditioner or solver.
|
||||
! x - complex(psb_dpk_), dimension(:), input.
|
||||
! The local part of the vector X.
|
||||
! beta - complex(psb_dpk_), input.
|
||||
! The scalar beta.
|
||||
! y - complex(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 trans='C','c' then op(K^(-1)) = K^(-C) (transpose conjugate of K^(-1)).
|
||||
! If prec%iprcparm(mld_smoother_sweeps_) > 1, the value of trans provided
|
||||
! in input is ignored.
|
||||
! work - complex(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_zsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
|
||||
|
||||
use psb_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_zsub_aply
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
type(mld_zbaseprec_type), intent(in) :: prec
|
||||
complex(psb_dpk_),intent(in) :: x(:)
|
||||
complex(psb_dpk_),intent(inout) :: y(:)
|
||||
complex(psb_dpk_),intent(in) :: alpha,beta
|
||||
character(len=1), intent(in) :: trans
|
||||
complex(psb_dpk_),target, intent(inout) :: work(:)
|
||||
integer, intent(out) :: info
|
||||
|
||||
! Local variables
|
||||
integer :: n_row,n_col
|
||||
complex(psb_dpk_), pointer :: ww(:), aux(:), tx(:),ty(:)
|
||||
integer :: ictxt,np,me,i, err_act
|
||||
character(len=20) :: name
|
||||
character :: trans_
|
||||
|
||||
name='mld_zsub_aply'
|
||||
info = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
|
||||
& a_err='complex(psb_dpk_)')
|
||||
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,0,0,0,0/),&
|
||||
& a_err='complex(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 /= 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 (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 = psb_err_from_subroutine_non_
|
||||
goto 9999
|
||||
endif
|
||||
|
||||
allocate(tx(n_col),ty(n_col),stat=info)
|
||||
if (info /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
|
||||
& a_err='complex(psb_dpk_)')
|
||||
goto 9999
|
||||
end if
|
||||
|
||||
tx = zzero
|
||||
ty = zzero
|
||||
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(-zone,prec%av(mld_ap_nd_),tx,zone,ty,&
|
||||
& prec%desc_data,info,work=aux,trans=trans_)
|
||||
|
||||
if (info /= psb_success_) exit
|
||||
|
||||
call mld_sub_solve(zone,prec,ty,zzero,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
|
||||
|
||||
deallocate(tx,ty,stat=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=(/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_zsub_aply
|
||||
|
||||
@ -1,325 +0,0 @@
|
||||
!!$
|
||||
!!$
|
||||
!!$ MLD2P4 version 2.0
|
||||
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
!!$ based on PSBLAS (Parallel Sparse BLAS version 3.0)
|
||||
!!$
|
||||
!!$ (C) Copyright 2008,2009,2010
|
||||
!!$
|
||||
!!$ 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.
|
||||
!!$
|
||||
!!$
|
||||
! File mld_zsub_solve.f90
|
||||
!
|
||||
! Subroutine: mld_zsub_solve
|
||||
! Version: complex
|
||||
!
|
||||
! This routine computes
|
||||
!
|
||||
! Y = beta*Y + alpha*op(K^(-1))*X,
|
||||
!
|
||||
! where
|
||||
! - K is a factored 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. approximate solution of a linear system
|
||||
!
|
||||
! A*Y = X,
|
||||
!
|
||||
! by using the L and U factors computed with an ILU factorization of A.
|
||||
! In this case K = L*U ~ A, alpha = 1 and beta = 0. The factors L and U
|
||||
! (and the matrix A) are either distributed and block-diagonal or replicated.
|
||||
!
|
||||
! 2. Solution of a linear system
|
||||
!
|
||||
! A*Y = X,
|
||||
!
|
||||
! by using the L and U factors computed with a LU factorization of A. In this
|
||||
! case K = L*U = A, alpha = 1 and beta = 0. The LU factorization is performed
|
||||
! by one of the following auxiliary pakages:
|
||||
! a. UMFPACK,
|
||||
! b. SuperLU,
|
||||
! c. SuperLU_Dist.
|
||||
! In the cases a. and b., the factors L and U (and the matrix A) are either
|
||||
! distributed and block diagonal) or replicated; in the case c., L, U (and A)
|
||||
! are distributed.
|
||||
!
|
||||
! This routine is used by mld_dsub_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.
|
||||
!
|
||||
!
|
||||
! Arguments:
|
||||
!
|
||||
! alpha - complex(psb_dpk_), input.
|
||||
! The scalar alpha.
|
||||
! prec - type(mld_zbaseprec_type), input.
|
||||
! The 'base preconditioner' data structure containing the local
|
||||
! part of the L and U factors of the matrix A.
|
||||
! x - complex(psb_dpk_), dimension(:), input.
|
||||
! The local part of the vector X.
|
||||
! beta - complex(psb_dpk_), input.
|
||||
! The scalar beta.
|
||||
! y - complex(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 trans='C','c' then op(K^(-1)) = K^(-C) (transpose conjugate of K^(-1)).
|
||||
! If prec%iprcparm(mld_smoother_sweeps_) > 1, the value of trans provided
|
||||
! in input is ignored.
|
||||
! work - complex(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_zsub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
|
||||
|
||||
use psb_sparse_mod
|
||||
use mld_inner_mod, mld_protect_name => mld_zsub_solve
|
||||
|
||||
implicit none
|
||||
|
||||
! Arguments
|
||||
type(psb_desc_type), intent(in) :: desc_data
|
||||
type(mld_zbaseprec_type), intent(in) :: prec
|
||||
complex(psb_dpk_),intent(in) :: x(:)
|
||||
complex(psb_dpk_),intent(inout) :: y(:)
|
||||
complex(psb_dpk_),intent(in) :: alpha,beta
|
||||
character(len=1), intent(in) :: trans
|
||||
complex(psb_dpk_),target, intent(inout) :: work(:)
|
||||
integer, intent(out) :: info
|
||||
|
||||
! Local variables
|
||||
integer :: n_row,n_col
|
||||
complex(psb_dpk_), pointer :: ww(:), aux(:), tx(:),ty(:)
|
||||
integer :: ictxt,np,me,i, err_act
|
||||
character(len=20) :: name
|
||||
character :: trans_
|
||||
|
||||
interface
|
||||
subroutine mld_zumf_solve(flag,m,x,b,n,ptr,info)
|
||||
use psb_sparse_mod
|
||||
integer, intent(in) :: flag,m,n,ptr
|
||||
integer, intent(out) :: info
|
||||
complex(psb_dpk_), intent(in) :: b(*)
|
||||
complex(psb_dpk_), intent(inout) :: x(*)
|
||||
end subroutine mld_zumf_solve
|
||||
end interface
|
||||
|
||||
name='mld_zsub_solve'
|
||||
info = psb_success_
|
||||
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(psb_err_iarg_invalid_i_,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 /= psb_success_) then
|
||||
info=psb_err_alloc_request_
|
||||
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
|
||||
& a_err='complex(psb_dpk_)')
|
||||
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,0,0,0,0/),&
|
||||
& a_err='complex(psb_dpk_)')
|
||||
goto 9999
|
||||
end if
|
||||
endif
|
||||
|
||||
|
||||
select case(prec%iprcparm(mld_sub_solve_))
|
||||
case(mld_ilu_n_,mld_milu_n_,mld_ilu_t_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with ILU(k)/MILU(k)/ILU(k,t)
|
||||
! factorization of the blocks (distributed matrix) or approximately
|
||||
! solve a system through ILU(k)/MILU(k)/ILU(k,t) (replicated matrix).
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
|
||||
call psb_spsm(zone,prec%av(mld_l_pr_),x,zzero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
|
||||
if (info == psb_success_) call psb_spsm(alpha,prec%av(mld_u_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_, work=aux)
|
||||
|
||||
case('T')
|
||||
call psb_spsm(zone,prec%av(mld_u_pr_),x,zzero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_, work=aux)
|
||||
if(info == psb_success_) call psb_spsm(alpha,prec%av(mld_l_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_,work=aux)
|
||||
|
||||
case('C')
|
||||
call psb_spsm(zone,prec%av(mld_u_pr_),x,zzero,ww,desc_data,info,&
|
||||
& trans=trans_,unit='L',diag=conjg(prec%d),choice=psb_none_, work=aux)
|
||||
if(info == psb_success_) call psb_spsm(alpha,prec%av(mld_l_pr_),ww,beta,y,desc_data,info,&
|
||||
& trans=trans_,unit='U',choice=psb_none_,work=aux)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in ILU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
case(mld_slu_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The SuperLU package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_zslu_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case('T')
|
||||
call mld_zslu_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case('C')
|
||||
call mld_zslu_solve(2,n_row,1,ww,n_row,prec%iprcparm(mld_slu_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLU subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case(mld_sludist_)
|
||||
!
|
||||
! Solve a distributed linear system with the LU factorization.
|
||||
! The SuperLU_DIST package is used.
|
||||
!
|
||||
|
||||
ww(1:n_row) = x(1:n_row)
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_zsludist_solve(0,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case('T')
|
||||
call mld_zsludist_solve(1,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case('C')
|
||||
call mld_zsludist_solve(2,n_row,1,ww,n_row,prec%iprcparm(mld_slud_ptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in SLUDist subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case (mld_umf_)
|
||||
!
|
||||
! Apply a block-Jacobi preconditioner with LU factorization of the
|
||||
! blocks (distributed matrix) or approximately solve a local linear
|
||||
! system through LU (replicated matrix). The UMFPACK package is used
|
||||
! to apply the LU factorization in both cases.
|
||||
!
|
||||
|
||||
select case(trans_)
|
||||
case('N')
|
||||
call mld_zumf_solve(0,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case('T')
|
||||
call mld_zumf_solve(1,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case('C')
|
||||
call mld_zumf_solve(2,n_row,ww,x,n_row,prec%iprcparm(mld_umf_numptr_),info)
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid TRANS in UMF subsolve')
|
||||
goto 9999
|
||||
end select
|
||||
|
||||
if (info == psb_success_) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
|
||||
|
||||
case default
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Invalid mld_sub_solve_')
|
||||
goto 9999
|
||||
|
||||
end select
|
||||
|
||||
if (info /= psb_success_) then
|
||||
call psb_errpush(psb_err_internal_error_,name,a_err='Error in subsolve ')
|
||||
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_zsub_solve
|
||||
|
||||
Loading…
Reference in New Issue