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MLPREC:

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Changed naming scheme for bjac_aply; refactored code to different
calling tree.
stopcriterion
Salvatore Filippone 17 years ago
parent f57aa144b9
commit 38ff0f0373
12 changed files with 1257 additions and 1177 deletions
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5
mlprec/Makefile
Unescape Escape View File

@ -15,13 +15,13 @@ F90OBJS=mld_das_bld.o mld_dslu_bld.o mld_dumf_bld.o mld_dilu0_fact.o\
mld_dprecbld.o mld_dprecfree.o mld_dprecset.o mld_dprecinit.o\
mld_dbaseprec_bld.o mld_ddiag_bld.o mld_daggrmap_bld.o \
mld_dprec_aply.o mld_dmlprec_aply.o mld_dslud_bld.o\
mld_dbaseprec_aply.o mld_dbjac_aply.o mld_das_aply.o mld_daggrmat_asb.o \
mld_dbaseprec_aply.o mld_dsub_aply.o mld_dsub_solve.o mld_das_aply.o mld_daggrmat_asb.o \
mld_zas_bld.o mld_zslu_bld.o mld_zumf_bld.o mld_zilu0_fact.o\
mld_zmlprec_bld.o mld_zsp_renum.o mld_zfact_bld.o mld_zilu_bld.o \
mld_zprecbld.o mld_zprecfree.o mld_zprecset.o mld_zprecinit.o \
mld_zbaseprec_bld.o mld_zdiag_bld.o mld_zaggrmap_bld.o \
mld_zprec_aply.o mld_zmlprec_aply.o mld_zslud_bld.o\
mld_zbaseprec_aply.o mld_zbjac_aply.o mld_zas_aply.o mld_zaggrmat_asb.o\
mld_zbaseprec_aply.o mld_zsub_aply.o mld_zsub_solve.o mld_zas_aply.o mld_zaggrmat_asb.o\
mld_diluk_fact.o mld_ziluk_fact.o mld_dilut_fact.o mld_zilut_fact.o \
$(MPFOBJS)
COBJS=mld_slu_impl.o mld_umf_impl.o mld_zslu_impl.o mld_zumf_impl.o
@ -40,6 +40,7 @@ lib: mpobjs $(OBJS)
$(F90OBJS) $(MPFOBJS): $(MODOBJS)
psb_prec_mod.o: mld_prec_mod.o
mld_prec_mod.o: mld_prec_type.o
$(MODOBJS): $(PSBLIBDIR)/psb_base_mod$(.mod)
mpobjs:
(make $(MPFOBJS) F90="$(MPF90)" F90COPT="$(F90COPT)")

12
mlprec/mld_das_aply.f90
Unescape Escape View File

@ -110,10 +110,10 @@ subroutine mld_das_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
case(mld_bjac_)
call mld_bjac_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
call mld_sub_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
if (info /= 0) then
info=4010
ch_err='mld_bjac_aply'
ch_err='mld_sub_aply'
goto 9999
end if
@ -126,10 +126,10 @@ subroutine mld_das_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
!
! Shortcut: this fixes performance for RAS(0) == BJA
!
call mld_bjac_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
call mld_sub_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
if(info /= 0) then
info=4010
ch_err='mld_bjac_aply'
ch_err='mld_sub_aply'
goto 9999
end if
@ -214,7 +214,7 @@ subroutine mld_das_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
! block-Jacobi solver can be applied at the coarsest level of a multilevel
! preconditioner). The resulting vector is ty.
!
call mld_bjac_aply(done,prec,tx,dzero,ty,prec%desc_data,trans_,aux,info)
call mld_sub_aply(done,prec,tx,dzero,ty,prec%desc_data,trans_,aux,info)
if(info /= 0) then
info=4010
ch_err='mld_bjac_aply'
@ -324,7 +324,7 @@ subroutine mld_das_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
! block-Jacobi solver can be applied at the coarsest level of a multilevel
! preconditioner). The resulting vector is ty.
!
call mld_bjac_aply(done,prec,tx,dzero,ty,prec%desc_data,trans_,aux,info)
call mld_sub_aply(done,prec,tx,dzero,ty,prec%desc_data,trans_,aux,info)
if(info /= 0) then
info=4010
ch_err='mld_bjac_aply'

555
mlprec/mld_dbjac_aply.f90
Unescape Escape View File

@ -1,555 +0,0 @@
!!$
!!$
!!$ MLD2P4
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS v.2.0)
!!$
!!$ (C) Copyright 2007 Alfredo Buttari University of Rome Tor Vergata
!!$ Pasqua D'Ambra ICAR-CNR, Naples
!!$ Daniela di Serafino Second University of Naples
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$
!!$ 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_dbjac_aply.f90
!
! Subroutine: mld_dbjac_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 trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
! Depending on K, alpha, 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_dbjac_bld and stored
! into the 'base preconditioner' data structure prec. See mld_dbjac_bld for more
! details.
!
! This routine is used by mld_dbaseprec_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.
!
! Inside mld_dbaseprec_aply, tasks 1, 3 and 4 may be selected if
! prec%iprcparm(smooth_sweeps_) = 1, while task 2 if prec%iprcparm(smooth_sweeps_)
! > 1. Furthermore, tasks 1, 2 and 3 may be performed if the matrix A is
! distributed among the processes (prec%iprcparm(mld_coarse_mat_) = mld_distr_mat_),
! while task 4 may be performed if A is replicated on the processes
! (prec%iprcparm(mld_coarse_mat_) = mld_repl_mat_). Note that the matrix A is
! distributed among the processes at each level of the multilevel preconditioner,
! except the coarsest one, where it may be either distributed or replicated on
! the processes. Furthermore, the tasks 2, 3 and 4 are performed only at the
! coarsest level. Note also that this routine manages implicitly the fact that
! the matrix is distributed or replicated, i.e. it does not make any explicit
! reference to the value of prec%iprcparm(mld_coarse_mat_).
!
!
! Arguments:
!
! alpha - real(kind(0.d0)), 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(kind(0.d0)), dimension(:), input.
! The local part of the vector X.
! beta - real(kind(0.d0)), input.
! The scalar beta.
! y - real(kind(0.d0)), 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(smooth_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - real(kind(0.d0)), dimension (:), target.
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
! info - integer, output.
! Error code.
!
subroutine mld_dbjac_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_mod, mld_protect_name => mld_dbjac_aply
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
type(mld_dbaseprc_type), intent(in) :: prec
real(kind(0.d0)),intent(in) :: x(:)
real(kind(0.d0)),intent(inout) :: y(:)
real(kind(0.d0)),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
real(kind(0.d0)),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
real(kind(1.d0)), 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)
integer, intent(in) :: flag,m,n,ptr
integer, intent(out) :: info
real(kind(1.d0)), intent(in) :: b(*)
real(kind(1.d0)), intent(inout) :: x(*)
end subroutine mld_dumf_solve
end interface
name='mld_dbjac_aply'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
if (n_col <= size(work)) then
ww => work(1:n_col)
if ((4*n_col+n_col) <= size(work)) then
aux => work(n_col+1:)
else
allocate(aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
endif
if (prec%iprcparm(mld_smooth_sweeps_) == 1) then
!
! TASKS 1, 3 and 4
!
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_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info == 0) 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(done,prec%av(mld_u_pr_),x,dzero,ww,desc_data,info,&
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info == 0) 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(4001,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(4001,name,a_err='Invalid TRANS in SLU subsolve')
goto 9999
end select
if (info ==0) 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(4001,name,a_err='Invalid TRANS in SLUDist subsolve')
goto 9999
end select
if (info == 0) 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(4001,name,a_err='Invalid TRANS in UMF subsolve')
goto 9999
end select
if (info == 0) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
case default
call psb_errpush(4001,name,a_err='Invalid mld_sub_solve_')
goto 9999
end select
if (info /= 0) then
call psb_errpush(4001,name,a_err='Error in subsolve Jacobi Sweeps = 1')
goto 9999
endif
else if (prec%iprcparm(mld_smooth_sweeps_) > 1) then
!
! TASK 2
!
! Apply prec%iprcparm(smooth_sweeps_) sweeps of a block-Jacobi solver
! to compute an approximate solution of a linear system.
!
! Note: trans is always 'N' here.
!
if (size(prec%av) < mld_ap_nd_) then
info = 4011
goto 9999
endif
allocate(tx(n_col),ty(n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
select case(prec%iprcparm(mld_sub_solve_))
case(mld_ilu_n_,mld_milu_n_,mld_ilu_t_)
!
! Use ILU(k)/MILU(k)/ILU(k,t) on the blocks.
!
select case(trans_)
case('N')
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_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)
if (info /=0) exit
call psb_spsm(done,prec%av(mld_l_pr_),ty,dzero,ww,&
& prec%desc_data,info,&
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info /=0) exit
call psb_spsm(done,prec%av(mld_u_pr_),ww,dzero,tx,&
& prec%desc_data,info,&
& trans=trans_,unit='U',choice=psb_none_,work=aux)
if (info /=0) exit
end do
case('T','C')
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(j+1) = D^(-1)*(X-ND*Y(j)), where D and ND are the
! block diagonal part and the remaining part of the local matrix
! and Y(j) is the approximate solution at sweep j.
!
ty(1:n_row) = x(1:n_row)
call psb_spmm(-done,prec%av(mld_ap_nd_),tx,done,ty,&
& prec%desc_data,info,work=aux,trans=trans_)
if (info /=0) exit
call psb_spsm(done,prec%av(mld_u_pr_),ty,dzero,ww,&
& prec%desc_data,info,&
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info /=0) exit
call psb_spsm(done,prec%av(mld_l_pr_),ww,dzero,tx,&
& prec%desc_data,info,&
& trans=trans_,unit='U',choice=psb_none_,work=aux)
if (info /=0) exit
end do
case default
call psb_errpush(4001,name,a_err='Invalid TRANS in ILU subsolve')
goto 9999
end select
case(mld_sludist_)
!
! Wrong choice: SuperLU_DIST
!
info = 4001
call psb_errpush(4001,name,a_err='Invalid SuperLU_DIST with Jacobi sweeps >1')
goto 9999
case(mld_slu_)
!
! Use the LU factorization from SuperLU.
!
select case(trans_)
case('N')
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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)
if(info /= 0) exit
call mld_dslu_solve(0,n_row,1,ty,n_row,prec%iprcparm(mld_slu_ptr_),info)
if(info /= 0) exit
tx(1:n_row) = ty(1:n_row)
end do
case('T','C')
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), where D and ND are the
! block diagonal part and the remaining part of the local matrix
! and Y(j) is the approximate solution at sweep j.
!
ty(1:n_row) = x(1:n_row)
call psb_spmm(-done,prec%av(mld_ap_nd_),tx,done,ty,&
& prec%desc_data,info,work=aux,trans=trans_)
if(info /= 0) exit
call mld_dslu_solve(1,n_row,1,ty,n_row,prec%iprcparm(mld_slu_ptr_),info)
if(info /= 0) exit
tx(1:n_row) = ty(1:n_row)
end do
case default
call psb_errpush(4001,name,a_err='Invalid TRANS in SLU subsolve')
goto 9999
end select
case(mld_umf_)
!
! Use the LU factorization from UMFPACK.
!
select case(trans_)
case('N')
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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)
if (info /= 0) exit
call mld_dumf_solve(0,n_row,ww,ty,n_row,&
& prec%iprcparm(mld_umf_numptr_),info)
if (info /= 0) exit
tx(1:n_row) = ww(1:n_row)
end do
case('T','C')
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), where D and ND are the
! block diagonal part and the remaining part of the local matrix
! and Y(j) is the approximate solution at sweep j.
!
ty(1:n_row) = x(1:n_row)
call psb_spmm(-done,prec%av(mld_ap_nd_),tx,done,ty,&
& prec%desc_data,info,work=aux,trans=trans_)
if (info /= 0) exit
call mld_dumf_solve(1,n_row,ww,ty,n_row,&
& prec%iprcparm(mld_umf_numptr_),info)
if (info /= 0) exit
tx(1:n_row) = ww(1:n_row)
end do
case default
call psb_errpush(4001,name,a_err='Invalid TRANS in UMF subsolve')
goto 9999
end select
case default
call psb_errpush(4001,name,a_err='Invalid mld_sub_solve_')
goto 9999
end select
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='subsolve with Jacobi sweeps > 1')
goto 9999
end if
!
! Put the result into the output vector Y.
!
call psb_geaxpby(alpha,tx,beta,y,desc_data,info)
deallocate(tx,ty,stat=info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='final cleanup with Jacobi sweeps > 1')
goto 9999
end if
else
info = 10
call psb_errpush(info,name,&
& i_err=(/2,prec%iprcparm(mld_smooth_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_dbjac_aply

2
mlprec/mld_dprecinit.f90
Unescape Escape View File

@ -235,7 +235,7 @@ subroutine mld_dprecinit(p,ptype,info,nlev)
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
p%baseprecv(ilev_)%iprcparm(mld_smooth_pos_) = mld_post_smooth_
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_umf_
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
p%baseprecv(ilev_)%iprcparm(mld_sub_fill_in_) = 0
p%baseprecv(ilev_)%iprcparm(mld_smooth_sweeps_) = 4
p%baseprecv(ilev_)%dprcparm(mld_aggr_damp_) = 4.d0/3.d0

297
mlprec/mld_dsub_aply.f90
Unescape Escape View File

@ -0,0 +1,297 @@
!!$
!!$
!!$ MLD2P4
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS v.2.0)
!!$
!!$ (C) Copyright 2007 Alfredo Buttari University of Rome Tor Vergata
!!$ Pasqua D'Ambra ICAR-CNR, Naples
!!$ Daniela di Serafino Second University of Naples
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$
!!$ 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 trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
! Depending on K, alpha, 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_dbjac_bld and stored
! into the 'base preconditioner' data structure prec. See mld_dbjac_bld for more
! details.
!
! This routine is used by mld_dbaseprec_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.
!
! Inside mld_dbaseprec_aply, tasks 1, 3 and 4 may be selected if
! prec%iprcparm(smooth_sweeps_) = 1, while task 2 if prec%iprcparm(smooth_sweeps_)
! > 1. Furthermore, tasks 1, 2 and 3 may be performed if the matrix A is
! distributed among the processes (prec%iprcparm(mld_coarse_mat_) = mld_distr_mat_),
! while task 4 may be performed if A is replicated on the processes
! (prec%iprcparm(mld_coarse_mat_) = mld_repl_mat_). Note that the matrix A is
! distributed among the processes at each level of the multilevel preconditioner,
! except the coarsest one, where it may be either distributed or replicated on
! the processes. Furthermore, the tasks 2, 3 and 4 are performed only at the
! coarsest level. Note also that this routine manages implicitly the fact that
! the matrix is distributed or replicated, i.e. it does not make any explicit
! reference to the value of prec%iprcparm(mld_coarse_mat_).
!
!
! Arguments:
!
! alpha - real(kind(0.d0)), 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(kind(0.d0)), dimension(:), input.
! The local part of the vector X.
! beta - real(kind(0.d0)), input.
! The scalar beta.
! y - real(kind(0.d0)), 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(smooth_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - real(kind(0.d0)), dimension (:), target.
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
! info - integer, output.
! Error code.
!
subroutine mld_dsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_mod, mld_protect_name => mld_dsub_aply
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
type(mld_dbaseprc_type), intent(in) :: prec
real(kind(0.d0)),intent(in) :: x(:)
real(kind(0.d0)),intent(inout) :: y(:)
real(kind(0.d0)),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
real(kind(0.d0)),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
real(kind(1.d0)), pointer :: ww(:), aux(:), tx(:),ty(:)
integer :: ictxt,np,me,i, err_act
character(len=20) :: name
character :: trans_
name='mld_dsub_aply'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
if (n_col <= size(work)) then
ww => work(1:n_col)
if ((4*n_col+n_col) <= size(work)) then
aux => work(n_col+1:)
else
allocate(aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
endif
if (prec%iprcparm(mld_smooth_sweeps_) == 1) then
call mld_sub_solve(alpha,prec,x,beta,y,desc_data,trans_,aux,info)
if (info /= 0) then
call psb_errpush(4001,name,a_err='Error in sub_aply Jacobi Sweeps = 1')
goto 9999
endif
else if (prec%iprcparm(mld_smooth_sweeps_) > 1) then
!
! TASK 2
!
! Apply prec%iprcparm(smooth_sweeps_) sweeps of a block-Jacobi solver
! to compute an approximate solution of a linear system.
!
! Note: trans is always 'N' here.
!
if (size(prec%av) < mld_ap_nd_) then
info = 4011
goto 9999
endif
allocate(tx(n_col),ty(n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
tx = dzero
ty = dzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(j+1) = D^(-1)*(X-ND*Y(j)), where D and ND are the
! block diagonal part and the remaining part of the local matrix
! and Y(j) is the approximate solution at sweep j.
!
ty(1:n_row) = x(1:n_row)
call psb_spmm(-done,prec%av(mld_ap_nd_),tx,done,ty,&
& prec%desc_data,info,work=aux,trans=trans_)
if (info /=0) exit
call mld_sub_solve(done,prec,ty,dzero,tx,desc_data,trans_,aux,info)
if (info /=0) exit
end do
if (info == 0) call psb_geaxpby(alpha,tx,beta,y,desc_data,info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='subsolve with Jacobi sweeps > 1')
goto 9999
end if
deallocate(tx,ty,stat=info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='final cleanup with Jacobi sweeps > 1')
goto 9999
end if
else
info = 10
call psb_errpush(info,name,&
& i_err=(/2,prec%iprcparm(mld_smooth_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

298
mlprec/mld_dsub_solve.f90
Unescape Escape View File

@ -0,0 +1,298 @@
!!$
!!$
!!$ MLD2P4
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS v.2.0)
!!$
!!$ (C) Copyright 2007 Alfredo Buttari University of Rome Tor Vergata
!!$ Pasqua D'Ambra ICAR-CNR, Naples
!!$ Daniela di Serafino Second University of Naples
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$
!!$ 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 trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
!
! 1. Solution of a linear system with sparse factors LU generated by means
! of an incomplete factorization approximating
!
! A*Y = X,
! In this case the factors of A are either distributed (in which case
! they are also block-diagonal) or replicated.
!
! 2. Solution of a linear system with sparse factors LU generated by means
! of an complete factorization
!
! A*Y = X,
!
! computed with the aid of an auxiliary sparse package such as
! a. UMFPACK
! b. SuperLU
! c. SuperLU_Dist
! In cases a. and b. the matrix A and its factors are either distributed
! and block diagonal or replicated; in case c. the matrix A and its
! factors are distributed.
!
!
! Arguments:
!
! alpha - real(kind(0.d0)), 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(kind(0.d0)), dimension(:), input.
! The local part of the vector X.
! beta - real(kind(0.d0)), input.
! The scalar beta.
! y - real(kind(0.d0)), 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(smooth_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - real(kind(0.d0)), 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_base_mod
use mld_prec_mod, mld_protect_name => mld_dsub_solve
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
type(mld_dbaseprc_type), intent(in) :: prec
real(kind(0.d0)),intent(in) :: x(:)
real(kind(0.d0)),intent(inout) :: y(:)
real(kind(0.d0)),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
real(kind(0.d0)),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
real(kind(1.d0)), 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)
integer, intent(in) :: flag,m,n,ptr
integer, intent(out) :: info
real(kind(1.d0)), intent(in) :: b(*)
real(kind(1.d0)), intent(inout) :: x(*)
end subroutine mld_dumf_solve
end interface
name='mld_dsub_solve'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
if (n_col <= size(work)) then
ww => work(1:n_col)
if ((4*n_col+n_col) <= size(work)) then
aux => work(n_col+1:)
else
allocate(aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='real(kind(1.d0))')
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_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info == 0) 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(done,prec%av(mld_u_pr_),x,dzero,ww,desc_data,info,&
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info == 0) 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(4001,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(4001,name,a_err='Invalid TRANS in SLU subsolve')
goto 9999
end select
if (info ==0) 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(4001,name,a_err='Invalid TRANS in SLUDist subsolve')
goto 9999
end select
if (info == 0) 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(4001,name,a_err='Invalid TRANS in UMF subsolve')
goto 9999
end select
if (info == 0) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
case default
call psb_errpush(4001,name,a_err='Invalid mld_sub_solve_')
goto 9999
end select
if (info /= 0) then
call psb_errpush(4001,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

39
mlprec/mld_prec_mod.f90
Unescape Escape View File

@ -260,8 +260,37 @@ module mld_prec_mod
end subroutine mld_zmlprec_aply
end interface
interface mld_bjac_aply
subroutine mld_dbjac_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
interface mld_sub_aply
subroutine mld_dsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_type
type(psb_desc_type), intent(in) :: desc_data
type(mld_dbaseprc_type), intent(in) :: prec
real(kind(0.d0)),intent(in) :: x(:)
real(kind(0.d0)),intent(inout) :: y(:)
real(kind(0.d0)),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
real(kind(0.d0)),target,intent(inout) :: work(:)
integer, intent(out) :: info
end subroutine mld_dsub_aply
subroutine mld_zsub_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_type
type(psb_desc_type), intent(in) :: desc_data
type(mld_zbaseprc_type), intent(in) :: prec
complex(kind(0.d0)),intent(in) :: x(:)
complex(kind(0.d0)),intent(inout) :: y(:)
complex(kind(0.d0)),intent(in) :: alpha,beta
character(len=1),intent(in) :: trans
complex(kind(0.d0)),target,intent(inout) :: work(:)
integer, intent(out) :: info
end subroutine mld_zsub_aply
end interface
interface mld_sub_solve
subroutine mld_dsub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_type
type(psb_desc_type), intent(in) :: desc_data
@ -272,8 +301,8 @@ module mld_prec_mod
character(len=1),intent(in) :: trans
real(kind(0.d0)),target,intent(inout) :: work(:)
integer, intent(out) :: info
end subroutine mld_dbjac_aply
subroutine mld_zbjac_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
end subroutine mld_dsub_solve
subroutine mld_zsub_solve(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_type
type(psb_desc_type), intent(in) :: desc_data
@ -284,7 +313,7 @@ module mld_prec_mod
character(len=1),intent(in) :: trans
complex(kind(0.d0)),target,intent(inout) :: work(:)
integer, intent(out) :: info
end subroutine mld_zbjac_aply
end subroutine mld_zsub_solve
end interface

16
mlprec/mld_zas_aply.f90
Unescape Escape View File

@ -110,10 +110,10 @@ subroutine mld_zas_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
case(mld_bjac_)
call mld_bjac_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
call mld_sub_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
if (info /= 0) then
info=4010
ch_err='mld_bjac_aply'
ch_err='mld_sub_aply'
goto 9999
end if
@ -126,10 +126,10 @@ subroutine mld_zas_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
!
! Shortcut: this fixes performance for RAS(0) == BJA
!
call mld_bjac_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
call mld_sub_aply(alpha,prec,x,beta,y,desc_data,trans_,work,info)
if(info /= 0) then
info=4010
ch_err='mld_bjac_aply'
ch_err='mld_sub_aply'
goto 9999
end if
@ -214,10 +214,10 @@ subroutine mld_zas_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
! block-Jacobi solver can be applied at the coarsest level of a multilevel
! preconditioner). The resulting vector is ty.
!
call mld_bjac_aply(zone,prec,tx,zzero,ty,prec%desc_data,trans_,aux,info)
call mld_sub_aply(zone,prec,tx,zzero,ty,prec%desc_data,trans_,aux,info)
if(info /= 0) then
info=4010
ch_err='mld_bjac_aply'
ch_err='mld_sub_aply'
goto 9999
end if
@ -324,10 +324,10 @@ subroutine mld_zas_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
! block-Jacobi solver can be applied at the coarsest level of a multilevel
! preconditioner). The resulting vector is ty.
!
call mld_bjac_aply(zone,prec,tx,zzero,ty,prec%desc_data,trans_,aux,info)
call mld_sub_aply(zone,prec,tx,zzero,ty,prec%desc_data,trans_,aux,info)
if(info /= 0) then
info=4010
ch_err='mld_bjac_aply'
ch_err='mld_sub_aply'
goto 9999
end if

599
mlprec/mld_zbjac_aply.f90
Unescape Escape View File

@ -1,599 +0,0 @@
!!$
!!$
!!$ MLD2P4
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS v.2.0)
!!$
!!$ (C) Copyright 2007 Alfredo Buttari University of Rome Tor Vergata
!!$ Pasqua D'Ambra ICAR-CNR, Naples
!!$ Daniela di Serafino Second University of Naples
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$
!!$ 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_zbjac_aply.f90
!
! Subroutine: mld_zbjac_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 trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
! Depending on K, alpha, 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_dbjac_bld and stored
! into the 'base preconditioner' data structure prec. See mld_dbjac_bld for more
! details.
!
! This routine is used by mld_dbaseprec_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.
!
! Inside mld_dbaseprec_aply, tasks 1, 3 and 4 may be selected if
! prec%iprcparm(smooth_sweeps_) = 1, while task 2 if prec%iprcparm(smooth_sweeps_)
! > 1. Furthermore, tasks 1, 2 and 3 may be performed if the matrix A is
! distributed among the processes (prec%iprcparm(mld_coarse_mat_) = mld_distr_mat_),
! while task 4 may be performed if A is replicated on the processes
! (prec%iprcparm(mld_coarse_mat_) = mld_repl_mat_). Note that the matrix A is
! distributed among the processes at each level of the multilevel preconditioner,
! except the coarsest one, where it may be either distributed or replicated on
! the processes. Furthermore, the tasks 2, 3 and 4 are performed only at the
! coarsest level. Note also that this routine manages implicitly the fact that
! the matrix is distributed or replicated, i.e. it does not make any explicit
! reference to the value of prec%iprcparm(mld_coarse_mat_).
!
!
! Arguments:
!
! alpha - complex(kind(0.d0)), 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(kind(0.d0)), dimension(:), input.
! The local part of the vector X.
! beta - complex(kind(0.d0)), input.
! The scalar beta.
! y - complex(kind(0.d0)), 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(smooth_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - complex(kind(0.d0)), dimension (:), target.
! Workspace. Its size must be at least 4*psb_cd_get_local_cols(desc_data).
! info - integer, output.
! Error code.
!
subroutine mld_zbjac_aply(alpha,prec,x,beta,y,desc_data,trans,work,info)
use psb_base_mod
use mld_prec_mod, mld_protect_name => mld_zbjac_aply
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
type(mld_zbaseprc_type), intent(in) :: prec
complex(kind(0.d0)),intent(in) :: x(:)
complex(kind(0.d0)),intent(inout) :: y(:)
complex(kind(0.d0)),intent(in) :: alpha,beta
character(len=1), intent(in) :: trans
complex(kind(0.d0)),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
complex(kind(1.d0)), 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)
integer, intent(in) :: flag,m,n,ptr
integer, intent(out) :: info
complex(kind(1.d0)), intent(in) :: b(*)
complex(kind(1.d0)), intent(inout) :: x(*)
end subroutine mld_zumf_solve
end interface
name='mld_zbjac_aply'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
if (n_col <= size(work)) then
ww => work(1:n_col)
if ((4*n_col+n_col) <= size(work)) then
aux => work(n_col+1:)
else
allocate(aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
endif
if (prec%iprcparm(mld_smooth_sweeps_) == 1) then
!
! TASKS 1, 3 and 4
!
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 == 0) 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(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 ==0) 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(4001,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(4001,name,a_err='Invalid TRANS in SLU subsolve')
goto 9999
end select
if (info ==0) 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(4001,name,a_err='Invalid TRANS in SLUDist subsolve')
goto 9999
end select
if (info == 0) 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(4001,name,a_err='Invalid TRANS in UMF subsolve')
goto 9999
end select
if (info == 0) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
case default
call psb_errpush(4001,name,a_err='Invalid mld_sub_solve_')
goto 9999
end select
if (info /= 0) then
call psb_errpush(4001,name,a_err='Error in subsolve Jacobi Sweeps = 1')
goto 9999
endif
else if (prec%iprcparm(mld_smooth_sweeps_) > 1) then
!
! TASK 2
!
! Apply prec%iprcparm(smooth_sweeps_) sweeps of a block-Jacobi solver
! to compute an approximate solution of a linear system.
!
! Note: trans is always 'N' here.
!
if (size(prec%av) < mld_ap_nd_) then
info = 4011
goto 9999
endif
allocate(tx(n_col),ty(n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
select case(prec%iprcparm(mld_sub_solve_))
case(mld_ilu_n_,mld_milu_n_,mld_ilu_t_)
!
! Use ILU(k)/MILU(k)/ILU(k,t) on the blocks.
!
select case(trans_)
case('N')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_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)
if (info /=0) exit
call psb_spsm(zone,prec%av(mld_l_pr_),ty,zzero,ww,&
& prec%desc_data,info,&
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info /=0) exit
call psb_spsm(zone,prec%av(mld_u_pr_),ww,zzero,tx,&
& prec%desc_data,info,&
& trans=trans_,unit='U',choice=psb_none_,work=aux)
if (info /=0) exit
end do
case('T','C')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_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 /=0) exit
call psb_spsm(zone,prec%av(mld_u_pr_),ty,zzero,ww,&
& prec%desc_data,info,&
& trans=trans_,unit='L',diag=prec%d,choice=psb_none_,work=aux)
if (info /=0) exit
call psb_spsm(zone,prec%av(mld_l_pr_),ww,zzero,tx,&
& prec%desc_data,info,&
& trans=trans_,unit='U',choice=psb_none_,work=aux)
if (info /=0) exit
end do
case default
call psb_errpush(4001,name,a_err='Invalid TRANS in ILU subsolve')
goto 9999
end select
case(mld_sludist_)
!
! Wrong choice: SuperLU_DIST
!
info = 4001
call psb_errpush(4001,name,a_err='Invalid SuperLU_DIST with Jacobi sweeps >1')
goto 9999
case(mld_slu_)
!
! Use the LU factorization from SuperLU.
!
select case(trans_)
case('N')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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)
if (info /= 0) exit
call mld_zslu_solve(0,n_row,1,ty,n_row,prec%iprcparm(mld_slu_ptr_),info)
if (info /= 0) exit
tx(1:n_row) = ty(1:n_row)
end do
case('T')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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 /= 0) exit
call mld_zslu_solve(1,n_row,1,ty,n_row,prec%iprcparm(mld_slu_ptr_),info)
if (info /= 0) exit
tx(1:n_row) = ty(1:n_row)
end do
case('C')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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 /= 0) exit
call mld_zslu_solve(2,n_row,1,ty,n_row,prec%iprcparm(mld_slu_ptr_),info)
if (info /= 0) exit
tx(1:n_row) = ty(1:n_row)
end do
case default
call psb_errpush(4001,name,a_err='Invalid TRANS in SLU subsolve')
goto 9999
end select
case(mld_umf_)
!
! Use the LU factorization from UMFPACK.
!
select case(trans_)
case('N')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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)
if (info /= 0) exit
call mld_zumf_solve(0,n_row,ww,ty,n_row,&
& prec%iprcparm(mld_umf_numptr_),info)
if (info /= 0) exit
tx(1:n_row) = ww(1:n_row)
end do
case('T')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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 /= 0) exit
call mld_zumf_solve(1,n_row,ww,ty,n_row,&
& prec%iprcparm(mld_umf_numptr_),info)
if (info /= 0) exit
tx(1:n_row) = ww(1:n_row)
end do
case('C')
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_sweeps_)
!
! Compute Y(k+1) = D^(-1)*(X-ND*Y(k)), 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 /= 0) exit
call mld_zumf_solve(2,n_row,ww,ty,n_row,&
& prec%iprcparm(mld_umf_numptr_),info)
if (info /= 0) exit
tx(1:n_row) = ww(1:n_row)
end do
case default
call psb_errpush(4001,name,a_err='Invalid TRANS in UMF subsolve')
goto 9999
end select
case default
call psb_errpush(4001,name,a_err='Invalid mld_sub_solve_')
goto 9999
end select
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='subsolve with Jacobi sweeps > 1')
goto 9999
end if
!
! Put the result into the output vector Y.
!
call psb_geaxpby(alpha,tx,beta,y,desc_data,info)
deallocate(tx,ty,stat=info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='final cleanup with Jacobi sweeps > 1')
goto 9999
end if
else
info = 10
call psb_errpush(info,name,&
& i_err=(/2,prec%iprcparm(mld_smooth_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_zbjac_aply

2
mlprec/mld_zprecinit.f90
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@ -235,7 +235,7 @@ subroutine mld_zprecinit(p,ptype,info,nlev)
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
p%baseprecv(ilev_)%iprcparm(mld_smooth_pos_) = mld_post_smooth_
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_umf_
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
p%baseprecv(ilev_)%iprcparm(mld_sub_fill_in_) = 0
p%baseprecv(ilev_)%iprcparm(mld_smooth_sweeps_) = 4
p%baseprecv(ilev_)%dprcparm(mld_aggr_damp_) = 4.d0/3.d0

298
mlprec/mld_zsub_aply.f90
Unescape Escape View File

@ -0,0 +1,298 @@
!!$
!!$
!!$ MLD2P4
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS v.2.0)
!!$
!!$ (C) Copyright 2007 Alfredo Buttari University of Rome Tor Vergata
!!$ Pasqua D'Ambra ICAR-CNR, Naples
!!$ Daniela di Serafino Second University of Naples
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$
!!$ 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 trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
! Depending on K, alpha, 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_dbjac_bld and stored
! into the 'base preconditioner' data structure prec. See mld_dbjac_bld for more
! details.
!
! This routine is used by mld_dbaseprec_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.
!
! Inside mld_dbaseprec_aply, tasks 1, 3 and 4 may be selected if
! prec%iprcparm(smooth_sweeps_) = 1, while task 2 if prec%iprcparm(smooth_sweeps_)
! > 1. Furthermore, tasks 1, 2 and 3 may be performed if the matrix A is
! distributed among the processes (prec%iprcparm(mld_coarse_mat_) = mld_distr_mat_),
! while task 4 may be performed if A is replicated on the processes
! (prec%iprcparm(mld_coarse_mat_) = mld_repl_mat_). Note that the matrix A is
! distributed among the processes at each level of the multilevel preconditioner,
! except the coarsest one, where it may be either distributed or replicated on
! the processes. Furthermore, the tasks 2, 3 and 4 are performed only at the
! coarsest level. Note also that this routine manages implicitly the fact that
! the matrix is distributed or replicated, i.e. it does not make any explicit
! reference to the value of prec%iprcparm(mld_coarse_mat_).
!
!
! Arguments:
!
! alpha - complex(kind(0.d0)), 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(kind(0.d0)), dimension(:), input.
! The local part of the vector X.
! beta - complex(kind(0.d0)), input.
! The scalar beta.
! y - complex(kind(0.d0)), 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(smooth_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - complex(kind(0.d0)), 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_base_mod
use mld_prec_mod, mld_protect_name => mld_zsub_aply
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
type(mld_zbaseprc_type), intent(in) :: prec
complex(kind(0.d0)),intent(in) :: x(:)
complex(kind(0.d0)),intent(inout) :: y(:)
complex(kind(0.d0)),intent(in) :: alpha,beta
character(len=1), intent(in) :: trans
complex(kind(0.d0)),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
complex(kind(1.d0)), pointer :: ww(:), aux(:), tx(:),ty(:)
integer :: ictxt,np,me,i, err_act
character(len=20) :: name
character :: trans_
name='mld_zsub_aply'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
if (n_col <= size(work)) then
ww => work(1:n_col)
if ((4*n_col+n_col) <= size(work)) then
aux => work(n_col+1:)
else
allocate(aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
endif
if (prec%iprcparm(mld_smooth_sweeps_) == 1) then
call mld_sub_solve(alpha,prec,x,beta,y,desc_data,trans_,aux,info)
if (info /= 0) then
call psb_errpush(4001,name,a_err='Error in sub_aply Jacobi Sweeps = 1')
goto 9999
endif
else if (prec%iprcparm(mld_smooth_sweeps_) > 1) then
!
! TASK 2
!
! Apply prec%iprcparm(smooth_sweeps_) sweeps of a block-Jacobi solver
! to compute an approximate solution of a linear system.
!
! Note: trans is always 'N' here.
!
if (size(prec%av) < mld_ap_nd_) then
info = 4011
goto 9999
endif
allocate(tx(n_col),ty(n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/2*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
tx = zzero
ty = zzero
do i=1, prec%iprcparm(mld_smooth_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 /=0) exit
call mld_sub_solve(zone,prec,ty,zzero,tx,desc_data,trans_,aux,info)
if (info /=0) exit
end do
if (info == 0) call psb_geaxpby(alpha,tx,beta,y,desc_data,info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='subsolve with Jacobi sweeps > 1')
goto 9999
end if
deallocate(tx,ty,stat=info)
if (info /= 0) then
info=4001
call psb_errpush(info,name,a_err='final cleanup with Jacobi sweeps > 1')
goto 9999
end if
else
info = 10
call psb_errpush(info,name,&
& i_err=(/2,prec%iprcparm(mld_smooth_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

311
mlprec/mld_zsub_solve.f90
Unescape Escape View File

@ -0,0 +1,311 @@
!!$
!!$
!!$ MLD2P4
!!$ MultiLevel Domain Decomposition Parallel Preconditioners Package
!!$ based on PSBLAS (Parallel Sparse BLAS v.2.0)
!!$
!!$ (C) Copyright 2007 Alfredo Buttari University of Rome Tor Vergata
!!$ Pasqua D'Ambra ICAR-CNR, Naples
!!$ Daniela di Serafino Second University of Naples
!!$ Salvatore Filippone University of Rome Tor Vergata
!!$
!!$ 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 trans,
! - X and Y are vectors,
! - alpha and beta are scalars.
!
!
! 1. Solution of a linear system with sparse factors LU generated by means
! of an incomplete factorization approximating
!
! A*Y = X,
! In this case the factors of A are either distributed (in which case
! they are also block-diagonal) or replicated.
!
! 2. Solution of a linear system with sparse factors LU generated by means
! of an complete factorization
!
! A*Y = X,
!
! computed with the aid of an auxiliary sparse package such as
! a. UMFPACK
! b. SuperLU
! c. SuperLU_Dist
! In cases a. and b. the matrix A and its factors are either distributed
! and block diagonal or replicated; in case c. the matrix A and its
! factors are distributed.
!
!
! Arguments:
!
! alpha - complex(kind(0.d0)), 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(kind(0.d0)), dimension(:), input.
! The local part of the vector X.
! beta - complex(kind(0.d0)), input.
! The scalar beta.
! y - complex(kind(0.d0)), 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(smooth_sweeps_) > 1, the value of trans provided
! in input is ignored.
! work - complex(kind(0.d0)), 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_base_mod
use mld_prec_mod, mld_protect_name => mld_zsub_solve
implicit none
! Arguments
type(psb_desc_type), intent(in) :: desc_data
type(mld_zbaseprc_type), intent(in) :: prec
complex(kind(0.d0)),intent(in) :: x(:)
complex(kind(0.d0)),intent(inout) :: y(:)
complex(kind(0.d0)),intent(in) :: alpha,beta
character(len=1), intent(in) :: trans
complex(kind(0.d0)),target, intent(inout) :: work(:)
integer, intent(out) :: info
! Local variables
integer :: n_row,n_col
complex(kind(1.d0)), 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)
integer, intent(in) :: flag,m,n,ptr
integer, intent(out) :: info
complex(kind(1.d0)), intent(in) :: b(*)
complex(kind(1.d0)), intent(inout) :: x(*)
end subroutine mld_zumf_solve
end interface
name='mld_zsub_solve'
info = 0
call psb_erractionsave(err_act)
ictxt=psb_cd_get_context(desc_data)
call psb_info(ictxt, me, np)
trans_ = toupper(trans)
select case(trans_)
case('N')
case('T','C')
case default
call psb_errpush(40,name)
goto 9999
end select
n_row = psb_cd_get_local_rows(desc_data)
n_col = psb_cd_get_local_cols(desc_data)
if (n_col <= size(work)) then
ww => work(1:n_col)
if ((4*n_col+n_col) <= size(work)) then
aux => work(n_col+1:)
else
allocate(aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/4*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
goto 9999
end if
endif
else
allocate(ww(n_col),aux(4*n_col),stat=info)
if (info /= 0) then
info=4025
call psb_errpush(info,name,i_err=(/5*n_col,0,0,0,0/),&
& a_err='complex(kind(1.d0))')
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 == 0) 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 ==0) 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 ==0) 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(4001,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(4001,name,a_err='Invalid TRANS in SLU subsolve')
goto 9999
end select
if (info ==0) 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(4001,name,a_err='Invalid TRANS in SLUDist subsolve')
goto 9999
end select
if (info == 0) 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(4001,name,a_err='Invalid TRANS in UMF subsolve')
goto 9999
end select
if (info == 0) call psb_geaxpby(alpha,ww,beta,y,desc_data,info)
case default
call psb_errpush(4001,name,a_err='Invalid mld_sub_solve_')
goto 9999
end select
if (info /= 0) then
call psb_errpush(4001,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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