diff --git a/docs/html/img107.png b/docs/html/img107.png
new file mode 100644
index 00000000..f2a61b67
Binary files /dev/null and b/docs/html/img107.png differ
diff --git a/docs/html/node12.html b/docs/html/node12.html
index d7166530..5a87fe5e 100644
--- a/docs/html/node12.html
+++ b/docs/html/node12.html
@@ -726,7 +726,7 @@ $w = y_1$;
\begin{tabbing}
\quad \=\quad...
...= y_l+r_l$\\
-\textbf{endfor} \\ [1mm]
+\textbf{endfor} [1mm]
$w = y_1$;
\end{tabbing}}
\end{minipage}}">
diff --git a/docs/html/node15.html b/docs/html/node15.html
index f7a2ff60..acb36212 100644
--- a/docs/html/node15.html
+++ b/docs/html/node15.html
@@ -163,10 +163,13 @@ preconditioner, which uses block Jacobi with ILU(0) on the
local blocks as post-smoother, has a coarsest matrix replicated on the processors,
and solves the coarsest-level system with the LU factorization from UMFPACK [9].
-Figure 4 shows how to set a three-level preconditioner similar to the one of 3, but the coarsest-level systems is solved with the multifrontal factorization from MUMPS [9].
-Note that MUMPS can be used on both replicated and distributed coarsest level matrices,
-as a global and local solver respectively.
+Figure 4 shows how to set a three-level preconditioner
+similar to the one of 3, but the coarsest-level
+systems is solved with the multifrontal factorization from
+MUMPS [9].
+Note that MUMPS can be used on both replicated and distributed
+coarsest level matrices, as a global and local solver respectively.
The number of levels is specified by using mld_precinit
; the other
preconditioner parameters are set by calling mld_precset
. Note that
the type of multilevel framework (i.e. multiplicative among the levels
@@ -183,13 +186,14 @@ solver. Again, mld_precset
is used only to set
non-default values of the parameters (see Tables 2-5).
In both cases, the construction and the application of the preconditioner
are carried out as for the default multi-level preconditioner.
-The code fragments shown in in Figures 3 4-5 are
-included in the example program file mld_dexample_ml.f90
too.
+The code fragments shown in in
+Figures 3 4-5 are
+included in the example program file mld_dexample_ml.f90
too.
Finally, Figure 6 shows the setup of a one-level
-additive Schwarz preconditioner, i.e. RAS with overlap 2. The corresponding
-example program is available in mld_dexample_
1lev.f90
.
+additive Schwarz preconditioner, i.e. RAS with overlap 2. The
+corresponding example program is available in mld_dexample_1lev.f90
.
For all the previous preconditioners, example programs where the sparse matrix and diff --git a/docs/html/node16.html b/docs/html/node16.html index d749e818..ad31029e 100644 --- a/docs/html/node16.html +++ b/docs/html/node16.html @@ -57,10 +57,11 @@ User Interface
-The basic user interface of MLD2P4 consists of six routines. The four routines mld_
precinit
,
-mld_precset
, mld_precbld
and mld_precaply
encapsulate all the functionalities
-for the setup and the application of any one-level and multi-level
-preconditioner implemented in the package.
+The basic user interface of MLD2P4 consists of six routines. The four
+routines mld_
precinit
, mld_precset
,
+mld_precbld
and mld_precaply
encapsulate all the
+functionalities for the setup and the application of any one-level and
+multi-level preconditioner implemented in the package.
The routine mld_precfree
deallocates the preconditioner data structure, while
mld_precdescr
prints a description of the preconditioner setup by the user.
diff --git a/docs/html/node18.html b/docs/html/node18.html
index 90842249..359e34bf 100644
--- a/docs/html/node18.html
+++ b/docs/html/node18.html
@@ -71,7 +71,7 @@ contained in val
.
The routine may also be invoked as a method
of the preconditioner object as in the following:
call p%set(what,val,info [,ilev])
+call p%set(what,val,info [,ilev, pos])
ilev
@@ -84,8 +84,8 @@ solver by extending one of the base MLD2P4 types, and has declared a
variable of the new type in the main program, it is possible to pass
the new smoother/solver variable to the setup routine as follows:
call p%set(smoother,info [,ilev])
-call p%set(solver,info [,ilev])
+call p%set(smoother,info [,ilev ,pos])
+call p%set(solver,info [,ilev ,poss])