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mld2p4-2:

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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
10 changed files with 4 additions and 2609 deletions
Show Stats Download Patch File Download Diff File

50
mlprec/Makefile
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@ -33,55 +33,13 @@ INNEROBJS= mld_dcoarse_bld.o mld_dmlprec_bld.o mld_dslu_bld.o \
mld_zilu0_fact.o mld_ziluk_fact.o mld_zilut_fact.o mld_zaggrmap_bld.o \ mld_zilu0_fact.o mld_ziluk_fact.o mld_zilut_fact.o mld_zaggrmap_bld.o \
mld_zmlprec_aply.o mld_zslud_bld.o mld_zaggrmat_asb.o \ mld_zmlprec_aply.o mld_zslud_bld.o mld_zaggrmat_asb.o \
$(MPFOBJS) $(MPFOBJS)
#
# MPFOBJS=mld_saggrmat_nosmth_asb.o mld_saggrmat_smth_asb.o \
# mld_daggrmat_nosmth_asb.o mld_daggrmat_smth_asb.o mld_daggrmat_minnrg_asb.o\
# mld_caggrmat_nosmth_asb.o mld_caggrmat_smth_asb.o \
# mld_zaggrmat_nosmth_asb.o mld_zaggrmat_smth_asb.o
# MPCOBJS=mld_sslud_interface.o mld_dslud_interface.o mld_cslud_interface.o mld_zslud_interface.o
# INNEROBJS=mld_scoarse_bld.o mld_dcoarse_bld.o \
# mld_ccoarse_bld.o mld_zcoarse_bld.o \
# mld_smlprec_bld.o mld_dmlprec_bld.o mld_cmlprec_bld.o mld_zmlprec_bld.o\
# mld_sas_bld.o mld_sslu_bld.o mld_sumf_bld.o mld_silu0_fact.o\
# mld_ssp_renum.o mld_sfact_bld.o mld_silu_bld.o \
# mld_sbaseprec_bld.o mld_sdiag_bld.o mld_saggrmap_bld.o \
# mld_smlprec_aply.o mld_sslud_bld.o\
# mld_sbaseprec_aply.o mld_ssub_aply.o mld_ssub_solve.o \
# mld_sas_aply.o mld_saggrmat_asb.o \
# mld_das_bld.o mld_dslu_bld.o mld_dumf_bld.o mld_dilu0_fact.o\
# mld_dsp_renum.o mld_dfact_bld.o mld_dilu_bld.o \
# mld_dbaseprec_bld.o mld_ddiag_bld.o mld_daggrmap_bld.o \
# mld_dmlprec_aply.o mld_dslud_bld.o\
# mld_dbaseprec_aply.o mld_dsub_aply.o mld_dsub_solve.o \
# mld_das_aply.o mld_daggrmat_asb.o \
# mld_cas_bld.o mld_cslu_bld.o mld_cumf_bld.o mld_cilu0_fact.o\
# mld_csp_renum.o mld_cfact_bld.o mld_cilu_bld.o \
# mld_cbaseprec_bld.o mld_cdiag_bld.o mld_caggrmap_bld.o \
# mld_cmlprec_aply.o mld_cslud_bld.o\
# mld_cbaseprec_aply.o mld_csub_aply.o mld_csub_solve.o \
# mld_cas_aply.o mld_caggrmat_asb.o\
# mld_zas_bld.o mld_zslu_bld.o mld_zumf_bld.o mld_zilu0_fact.o\
# mld_zsp_renum.o mld_zfact_bld.o mld_zilu_bld.o \
# mld_zbaseprec_bld.o mld_zdiag_bld.o mld_zaggrmap_bld.o \
# mld_zmlprec_aply.o mld_zslud_bld.o\
# mld_zbaseprec_aply.o mld_zsub_aply.o mld_zsub_solve.o \
# mld_zas_aply.o mld_zaggrmat_asb.o\
# mld_siluk_fact.o mld_ciluk_fact.o mld_silut_fact.o mld_cilut_fact.o \
# mld_diluk_fact.o mld_ziluk_fact.o mld_dilut_fact.o mld_zilut_fact.o \
# $(MPFOBJS)
OUTEROBJS=mld_dprecbld.o mld_dprecset.o mld_dprecinit.o mld_dprecaply.o \ OUTEROBJS=mld_dprecbld.o mld_dprecset.o mld_dprecinit.o mld_dprecaply.o \
mld_sprecbld.o mld_sprecset.o mld_sprecinit.o mld_sprecaply.o \ mld_sprecbld.o mld_sprecset.o mld_sprecinit.o mld_sprecaply.o \
mld_cprecbld.o mld_cprecset.o mld_cprecinit.o mld_cprecaply.o \ mld_cprecbld.o mld_cprecset.o mld_cprecinit.o mld_cprecaply.o \
mld_zprecbld.o mld_zprecset.o mld_zprecinit.o mld_zprecaply.o mld_zprecbld.o mld_zprecset.o mld_zprecinit.o mld_zprecaply.o
#OUTEROBJS=mld_sprecbld.o mld_sprecset.o mld_sprecinit.o\
# mld_sprecaply.o \
# mld_dprecbld.o mld_dprecset.o mld_dprecinit.o\
# mld_dprecaply.o \
# mld_cprecbld.o mld_cprecset.o mld_cprecinit.o\
# mld_cprecaply.o \
# mld_zprecbld.o mld_zprecset.o mld_zprecinit.o \
# mld_zprecaply.o
F90OBJS=$(OUTEROBJS) $(INNEROBJS) F90OBJS=$(OUTEROBJS) $(INNEROBJS)
COBJS= mld_sslu_interface.o mld_sumf_interface.o \ COBJS= mld_sslu_interface.o mld_sumf_interface.o \
@ -109,11 +67,11 @@ mld_prec_type.o: mld_s_prec_type.o mld_d_prec_type.o mld_c_prec_type.o mld_z_pre
mld_prec_mod.o mld_innner_mod.o: mld_prec_type.o mld_prec_mod.o mld_innner_mod.o: mld_prec_type.o
mld_inner_mod.o: mld_move_alloc_mod.o mld_inner_mod.o: mld_move_alloc_mod.o
mld_move_alloc_mod.o: mld_prec_type.o mld_move_alloc_mod.o: mld_prec_type.o
mld_d_diag_solver.o mld_d_ilu_solver.o: mld_d_prec_type.o mld_d_umf_solver.o mld_d_diag_solver.o mld_d_ilu_solver.o: mld_d_prec_type.o
mld_d_as_smoother.o mld_d_jac_smoother.o: mld_d_prec_type.o mld_d_as_smoother.o mld_d_jac_smoother.o: mld_d_prec_type.o
mld_d_jac_smoother.o: mld_d_diag_solver.o mld_d_jac_smoother.o: mld_d_diag_solver.o
mld_dprecinit.o mld_dprecset.o: mld_d_diag_solver.o mld_d_ilu_solver.o \ mld_dprecinit.o mld_dprecset.o: mld_d_diag_solver.o mld_d_ilu_solver.o \
mld_d_as_smoother.o mld_d_jac_smoother.o mld_d_umf_solver.o mld_d_as_smoother.o mld_d_jac_smoother.o
$(MODOBJS): $(PSBINCDIR)/psb_sparse_mod$(.mod) $(MODOBJS): $(PSBINCDIR)/psb_sparse_mod$(.mod)

296
mlprec/mld_csub_aply.f90
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@ -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_csub_aply.f90
!
! Subroutine: mld_csub_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_spk_), input.
! The scalar alpha.
! prec - type(mld_cbaseprec_type), input.
! The 'base preconditioner' data structure containing the local
! part of the preconditioner or solver.
! x - complex(psb_spk_), dimension(:), input.
! The local part of the vector X.
! beta - complex(psb_spk_), input.
! The scalar beta.
! y - complex(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 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_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_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod
use mld_inner_mod, mld_protect_name => mld_csub_aply
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_
name='mld_csub_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_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
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_spk_)')
goto 9999
end if
tx = czero
ty = czero
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(-cone,prec%av(mld_ap_nd_),tx,cone,ty,&
& prec%desc_data,info,work=aux,trans=trans_)
if (info /= psb_success_) exit
call mld_sub_solve(cone,prec,ty,czero,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_csub_aply

324
mlprec/mld_csub_solve.f90
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@ -1,324 +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_csub_solve.f90
!
! Subroutine: mld_csub_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_spk_), input.
! The scalar alpha.
! prec - type(mld_cbaseprec_type), input.
! The 'base preconditioner' data structure containing the local
! part of the L and U factors of the matrix A.
! x - complex(psb_spk_), dimension(:), input.
! The local part of the vector X.
! beta - complex(psb_spk_), input.
! The scalar beta.
! y - complex(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 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_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

296
mlprec/mld_dsub_aply.f90
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@ -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

312
mlprec/mld_dsub_solve.f90
Unescape Escape View File

@ -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

104
mlprec/mld_inner_mod.f90
Unescape Escape View File

@ -245,110 +245,6 @@ module mld_inner_mod
end interface end interface
interface mld_sub_aply
subroutine mld_ssub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_sspmat_type, psb_desc_type, psb_spk_
use mld_prec_type, only : mld_sbaseprec_type
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
end subroutine mld_ssub_aply
subroutine mld_dsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_dspmat_type, psb_desc_type, psb_dpk_
use mld_prec_type, only : mld_dbaseprec_type
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
end subroutine mld_dsub_aply
subroutine mld_csub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_cspmat_type, psb_desc_type, psb_spk_
use mld_prec_type, only : mld_cbaseprec_type
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
end subroutine mld_csub_aply
subroutine mld_zsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_zspmat_type, psb_desc_type, psb_dpk_
use mld_prec_type, only : mld_zbaseprec_type
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
end subroutine mld_zsub_aply
end interface
interface mld_sub_solve
subroutine mld_ssub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_sspmat_type, psb_desc_type, psb_spk_
use mld_prec_type, only : mld_sbaseprec_type
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
end subroutine mld_ssub_solve
subroutine mld_dsub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_dspmat_type, psb_desc_type, psb_dpk_
use mld_prec_type, only : mld_dbaseprec_type
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
end subroutine mld_dsub_solve
subroutine mld_csub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_cspmat_type, psb_desc_type, psb_spk_
use mld_prec_type, only : mld_cbaseprec_type
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
end subroutine mld_csub_solve
subroutine mld_zsub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_sparse_mod, only : psb_zspmat_type, psb_desc_type, psb_dpk_
use mld_prec_type, only : mld_zbaseprec_type
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
end subroutine mld_zsub_solve
end interface
interface mld_asmat_bld interface mld_asmat_bld
Subroutine mld_sasmat_bld(ptype,novr,a,blk,desc_data,upd,desc_p,info,outfmt) Subroutine mld_sasmat_bld(ptype,novr,a,blk,desc_data,upd,desc_p,info,outfmt)
use psb_sparse_mod, only : psb_sspmat_type, psb_desc_type, psb_spk_ use psb_sparse_mod, only : psb_sspmat_type, psb_desc_type, psb_spk_

297
mlprec/mld_ssub_aply.f90
Unescape Escape View File

@ -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

312
mlprec/mld_ssub_solve.f90
Unescape Escape View File

@ -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

297
mlprec/mld_zsub_aply.f90
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@ -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

325
mlprec/mld_zsub_solve.f90
Unescape Escape View File

@ -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
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