Fixes from Pasqua

docs/src/gettingstarted.tex

@@ -219,7 +219,7 @@ Furthermore, specifying block-Jacobi as coarsest-level
 solver implies that the coarsest-level matrix is distributed
 among the processes.
 Figure~\ref{fig:ex3} shows how to set a W-cycle preconditioner which
-applies no pre-smoother and 2 Gauss-Seidel sweeps as post-smoother,
+applies 2 Gauss-Seidel sweeps as pre- and post-smoother,
 and solves the coarsest-level system with the multifrontal LU factorization
 implemented in MUMPS. It is specified that the coarsest-level
 matrix is distributed, since MUMPS can be used on both
@@ -227,14 +227,14 @@ replicated and distributed matrices, and by default
 it is used on replicated ones. Note the use of the parameter \verb|pos|
 to specify a property only for the pre-smoother or the post-smoother
 (see Section~\ref{sec:precset} for more details).
-Note also that a Krylov method different from CG must be used to solve
-the preconditioned system, since the preconditione in nonsymmetric.
 The code fragments shown in Figures~\ref{fig:ex2} and \ref{fig:ex3} are
 included in the example program file \verb|mld_dexample_ml.f90| too.
 
 Finally, Figure~\ref{fig:ex4} shows the setup of a one-level
-additive Schwarz preconditioner, i.e., RAS with overlap 2. The
-corresponding example program is available in the file
+additive Schwarz preconditioner, i.e., RAS with overlap 2.
+Note also that a Krylov method different from CG must be used to solve
+the preconditioned system, since the preconditione in nonsymmetric.
+The corresponding example program is available in the file
 \verb|mld_dexample_1lev.f90|. 
 
 For all the previous preconditioners, example programs where the sparse matrix and
@@ -282,20 +282,18 @@ boundary conditions are also available in the directory \verb|examples/pdegen|.
 \begin{verbatim}
 ... ...
 ! build a W-cycle preconditioner with 2 Gauss-Seidel sweeps as 
-! post-smoother (and no pre-smoother), a distributed coarsest
+! pre- and post-smoother, a distributed coarsest
 ! matrix, and MUMPS as coarsest-level solver
   call P%init('ML',info)
   call P%set('ML_TYPE','WCYCLE',info)
   call P%set('SMOOTHER_TYPE','GS',info)
-  call P%set('SMOOTHER_SWEEPS',0,info,pos='PRE')
+  call P%set('SMOOTHER_SWEEPS',2,info,pos='PRE')
   call P%set('SMOOTHER_SWEEPS',2,info,pos='POST')
   call P%set('COARSE_SOLVE','MUMPS',info)
   call P%set('COARSE_MAT','DIST',info)
   call P%hierarchy_build(A,desc_A,info)
   call P%smoothers_build(A,desc_A,info)
 ... ...
-! solve Ax=b with preconditioned BiCGSTAB
-  call psb_krylov('BICGSTAB',A,P,b,x,tol,desc_A,info)
 \end{verbatim}
 }
 \end{minipage}
@@ -314,6 +312,8 @@ boundary conditions are also available in the directory \verb|examples/pdegen|.
   call P%set('SUB_OVR',2,info)
   call P%bld(A,desc_A,info)
 ... ...
+! solve Ax=b with preconditioned BiCGSTAB
+  call psb_krylov('BICGSTAB',A,P,b,x,tol,desc_A,info)
 \end{verbatim}
 }
 \end{minipage}

examples/fileread/mld_dexample_ml.f90

@@ -53,7 +53,7 @@
 ! sweeps (with ILU(0) on the blocks) as coarsest-level solver(Sec. 5.1, Fig. 3)
 !
 ! - choice = 3, build a W-cycle preconditioner with 2 Gauss-Seidel sweeps as
-! post-smoother (and no pre-smoother), a distributed coarsest
+! pre- and post-smoother, a distributed coarsest
 ! matrix, and MUMPS as coarsest-level solver (Sec. 5.1, Fig. 4)
 !
 ! The matrix and the rhs are read from files (if an rhs is not available, the
@@ -238,11 +238,11 @@ program mld_dexample_ml
     call P%init('ML',info)
     call P%set('ML_TYPE','WCYCLE',info)
     call P%set('SMOOTHER_TYPE','GS',info)
-    call P%set('SMOOTHER_SWEEPS',0,info,pos='PRE')
+    call P%set('SMOOTHER_SWEEPS',2,info,pos='PRE')
     call P%set('SMOOTHER_SWEEPS',2,info,pos='POST')
     call P%set('COARSE_SOLVE','MUMPS',info)
     call P%set('COARSE_MAT','DIST',info)
-    kmethod = 'BICGSTAB'
+    kmethod = 'CG'
   end select
 
   ! build the preconditioner
@@ -267,7 +267,7 @@ program mld_dexample_ml
   call x%zero()
   call psb_geasb(x,desc_A,info)
 
-  ! solve Ax=b with preconditioned BiCGSTAB
+  ! solve Ax=b with preconditioned CG
 
   call psb_barrier(ictxt)
   t1 = psb_wtime()