Fixed docs.

stopcriterion
Salvatore Filippone 7 years ago
parent 4b43164668
commit b7e8a921d8

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@ -80,25 +80,25 @@ where <!-- MATH
$A=(a_{ij}) \in \mathbb{R}^{n \times n}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="137" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
WIDTH="137" HEIGHT="38" ALIGN="MIDDLE" BORDER="0"
SRC="img5.png"
ALT="$A=(a_{ij}) \in \mathbb{R}^{n \times n}$"></SPAN> is a nonsingular sparse matrix;
for ease of presentation we assume <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img3.png"
ALT="$A$"></SPAN> has a symmetric sparsity
pattern.
</BIG></BIG></BIG>
<P>
<BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">Let us consider as finest index space the set of row (column) indices of <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img3.png"
ALT="$A$"></SPAN>, i.e.,
<!-- MATH
$\Omega = \{1, 2, \ldots, n\}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="131" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
WIDTH="132" HEIGHT="36" ALIGN="MIDDLE" BORDER="0"
SRC="img6.png"
ALT="$\Omega = \{1, 2, \ldots, n\}$"></SPAN>.
Any algebraic multilevel preconditioners implemented in MLD2P4 generates
@ -122,39 +122,39 @@ a hierarchy of index spaces and a corresponding hierarchy of matrices,
<BR CLEAR="ALL">
<P></P><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">
by using the information contained in <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img3.png"
ALT="$A$"></SPAN>, without assuming any
knowledge of the geometry of the problem from which <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img3.png"
ALT="$A$"></SPAN> originates.
A vector space <!-- MATH
$\mathbb{R}^{n_{k}}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="33" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="34" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img8.png"
ALT="$\mathbb{R}^{n_{k}}$"></SPAN> is associated with <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN>,
where <SPAN CLASS="MATH"><IMG
WIDTH="23" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
SRC="img10.png"
ALT="$n_k$"></SPAN> is the size of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN>.
For all <SPAN CLASS="MATH"><IMG
WIDTH="71" HEIGHT="32" ALIGN="MIDDLE" BORDER="0"
WIDTH="70" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
SRC="img11.png"
ALT="$k &lt; nlev$"></SPAN>, a restriction operator and a prolongation one are built,
which connect two levels <SPAN CLASS="MATH"><IMG
WIDTH="14" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="14" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img12.png"
ALT="$k$"></SPAN> and <SPAN CLASS="MATH"><IMG
WIDTH="44" HEIGHT="32" ALIGN="MIDDLE" BORDER="0"
WIDTH="44" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
SRC="img13.png"
ALT="$k+1$"></SPAN>:
</BIG></BIG></BIG>
@ -168,7 +168,7 @@ P^k \in \mathbb{R}^{n_k \times n_{k+1}}, \quad
-->
<IMG
WIDTH="255" HEIGHT="30" BORDER="0"
WIDTH="253" HEIGHT="30" BORDER="0"
SRC="img14.png"
ALT="\begin{displaymath}
P^k \in \mathbb{R}^{n_k \times n_{k+1}}, \quad
@ -178,7 +178,7 @@ R^k \in \mathbb{R}^{n_{k+1}\times n_k};
<BR CLEAR="ALL">
<P></P><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">
the matrix <SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="43" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img15.png"
ALT="$A^{k+1}$"></SPAN> is computed by using the previous operators according
to the Galerkin approach, i.e.,
@ -192,7 +192,7 @@ A^{k+1}=R^kA^kP^k.
-->
<IMG
WIDTH="131" HEIGHT="28" BORDER="0"
WIDTH="129" HEIGHT="27" BORDER="0"
SRC="img16.png"
ALT="\begin{displaymath}
A^{k+1}=R^kA^kP^k.
@ -205,22 +205,22 @@ In the current implementation of MLD2P4 we have <SPAN CLASS="MATH"><IMG
SRC="img17.png"
ALT="$R^k=(P^k)^T$"></SPAN>
A smoother with iteration matrix <SPAN CLASS="MATH"><IMG
WIDTH="31" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="32" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img18.png"
ALT="$M^k$"></SPAN> is set up at each level <SPAN CLASS="MATH"><IMG
WIDTH="71" HEIGHT="32" ALIGN="MIDDLE" BORDER="0"
WIDTH="70" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
SRC="img11.png"
ALT="$k &lt; nlev$"></SPAN>, and a solver
is set up at the coarsest level, so that they are ready for application
(for example, setting up a solver based on the <SPAN CLASS="MATH"><IMG
WIDTH="30" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="30" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img19.png"
ALT="$LU$"></SPAN> factorization means computing
and storing the <SPAN CLASS="MATH"><IMG
WIDTH="16" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img20.png"
ALT="$L$"></SPAN> and <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img21.png"
ALT="$U$"></SPAN> factors). The construction of the hierarchy of AMG components
described so far corresponds to the so-called build phase of the preconditioner.
@ -262,8 +262,8 @@ end
\begin{tabbing}
\quad \=\quad \=\quad...
...[1mm]
\&gt;endif [1mm]
\&gt;return $u^k$ [1mm]
\&gt;endif \\ [1mm]
\&gt;return $u^k$\ \\ [1mm]
end
\end{tabbing}\end{minipage}}">
@ -276,7 +276,7 @@ end
to obtain different multilevel preconditioners;
this is done in the application phase, i.e., in the computation of a vector
of type <SPAN CLASS="MATH"><IMG
WIDTH="81" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="82" HEIGHT="21" ALIGN="BOTTOM" BORDER="0"
SRC="img23.png"
ALT="$w=B^{-1}v$"></SPAN>, where <SPAN CLASS="MATH"><IMG
WIDTH="19" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"

@ -54,11 +54,11 @@ Smoothed Aggregation
</H2><BIG CLASS="LARGE"><BIG CLASS="LARGE"></BIG></BIG>
<P>
<BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">In order to define the prolongator <SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img25.png"
ALT="$P^k$"></SPAN>, used to compute
the coarse-level matrix <SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="43" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img15.png"
ALT="$A^{k+1}$"></SPAN>, MLD2P4 uses the smoothed aggregation
algorithm described in [<A
@ -66,15 +66,15 @@ algorithm described in [<A
HREF="node36.html#VANEK_MANDEL_BREZINA">26</A>].
The basic idea of this algorithm is to build a coarse set of indices
<SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="43" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img26.png"
ALT="$\Omega^{k+1}$"></SPAN> by suitably grouping the indices of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN> into disjoint
subsets (aggregates), and to define the coarse-to-fine space transfer operator
<SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img25.png"
ALT="$P^k$"></SPAN> by applying a suitable smoother to a simple piecewise constant
prolongation operator, with the aim of improving the quality of the coarse-space correction.
@ -84,26 +84,26 @@ prolongation operator, with the aim of improving the quality of the coarse-space
</BIG></BIG></BIG>
<OL>
<LI>aggregation of the indices of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN> to obtain <SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="43" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img26.png"
ALT="$\Omega^{k+1}$"></SPAN>;
</LI>
<LI>construction of the prolongator <SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img25.png"
ALT="$P^k$"></SPAN>;
</LI>
<LI>application of <SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img25.png"
ALT="$P^k$"></SPAN> and <SPAN CLASS="MATH"><IMG
WIDTH="95" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img17.png"
ALT="$R^k=(P^k)^T$"></SPAN> to build <SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="43" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img15.png"
ALT="$A^{k+1}$"></SPAN>.
</LI>
@ -116,13 +116,13 @@ each index <!-- MATH
$j \in \Omega^{k+1}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="71" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="72" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img27.png"
ALT="$j \in \Omega^{k+1}$"></SPAN> corresponds to an aggregate <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img28.png"
ALT="$\Omega^k_j$"></SPAN> of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN>,
consisting of a suitably chosen index <!-- MATH
@ -133,7 +133,7 @@ consisting of a suitably chosen index <!-- MATH
SRC="img29.png"
ALT="$i \in \Omega^k$"></SPAN> and indices that are (usually) contained in a
strongly-coupled neighborood of <SPAN CLASS="MATH"><IMG
WIDTH="10" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="11" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img30.png"
ALT="$i$"></SPAN>, i.e.,
</BIG></BIG></BIG>
@ -149,7 +149,7 @@ strongly-coupled neighborood of <SPAN CLASS="MATH"><IMG
<A NAME="eq:strongly_coup"></A>
<TABLE WIDTH="100%" ALIGN="CENTER">
<TR VALIGN="MIDDLE"><TD ALIGN="CENTER" NOWRAP><A NAME="eq:strongly_coup"></A><IMG
WIDTH="387" HEIGHT="49" BORDER="0"
WIDTH="387" HEIGHT="48" BORDER="0"
SRC="img31.png"
ALT="\begin{displaymath}
\Omega^k_j \subset \mathcal{N}_i^k(\theta) =
@ -164,7 +164,7 @@ for a given threshold <!-- MATH
$\theta \in [0,1]$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="69" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
WIDTH="69" HEIGHT="36" ALIGN="MIDDLE" BORDER="0"
SRC="img32.png"
ALT="$\theta \in [0,1]$"></SPAN> (see&nbsp;[<A
HREF="node36.html#VANEK_MANDEL_BREZINA">26</A>] for the details).
@ -175,7 +175,7 @@ distribution. This version is embarrassingly parallel, since it does not require
communication. On the other hand, it may produce some nonuniform aggregates
and is strongly dependent on the number of processors and on the initial partitioning
of the matrix <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img3.png"
ALT="$A$"></SPAN>. Nevertheless, this parallel algorithm has been chosen for
MLD2P4, since it has been shown to produce good results in practice
@ -186,7 +186,7 @@ MLD2P4, since it has been shown to produce good results in practice
</BIG></BIG></BIG>
<P>
<BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">The prolongator <SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img25.png"
ALT="$P^k$"></SPAN> is built starting from a tentative prolongator
<!-- MATH
@ -212,7 +212,7 @@ MLD2P4, since it has been shown to produce good results in practice
<A NAME="eq:tent_prol"></A>
<TABLE WIDTH="100%" ALIGN="CENTER">
<TR VALIGN="MIDDLE"><TD ALIGN="CENTER" NOWRAP><A NAME="eq:tent_prol"></A><IMG
WIDTH="286" HEIGHT="52" BORDER="0"
WIDTH="286" HEIGHT="51" BORDER="0"
SRC="img34.png"
ALT="\begin{displaymath}
\bar{P}^k =(\bar{p}_{ij}^k), \quad \bar{p}_{ij}^k =
@ -229,21 +229,21 @@ where <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img28.png"
ALT="$\Omega^k_j$"></SPAN> is the aggregate of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN>
corresponding to the index <!-- MATH
$j \in \Omega^{k+1}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="71" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="72" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img27.png"
ALT="$j \in \Omega^{k+1}$"></SPAN>.
<SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img25.png"
ALT="$P^k$"></SPAN> is obtained by applying to <SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img35.png"
ALT="$\bar{P}^k$"></SPAN> a smoother
<!-- MATH
@ -263,7 +263,7 @@ P^k = S^k \bar{P}^k,
-->
<IMG
WIDTH="91" HEIGHT="30" BORDER="0"
WIDTH="90" HEIGHT="30" BORDER="0"
SRC="img37.png"
ALT="\begin{displaymath}
P^k = S^k \bar{P}^k,
@ -277,7 +277,7 @@ method&nbsp;[<A
HREF="node36.html#BREZINA_VANEK">2</A>,<A
HREF="node36.html#Stuben_01">24</A>].
A simple choice for <SPAN CLASS="MATH"><IMG
WIDTH="24" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img38.png"
ALT="$S^k$"></SPAN> is the damped Jacobi smoother:
</BIG></BIG></BIG>
@ -290,7 +290,7 @@ S^k = I - \omega^k (D^k)^{-1} A^k_F ,
-->
<IMG
WIDTH="176" HEIGHT="32" BORDER="0"
WIDTH="175" HEIGHT="31" BORDER="0"
SRC="img39.png"
ALT="\begin{displaymath}
S^k = I - \omega^k (D^k)^{-1} A^k_F ,
@ -299,17 +299,17 @@ S^k = I - \omega^k (D^k)^{-1} A^k_F ,
<BR CLEAR="ALL">
<P></P><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">
where <SPAN CLASS="MATH"><IMG
WIDTH="28" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="28" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img40.png"
ALT="$D^k$"></SPAN> is the diagonal matrix with the same diagonal entries as <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img41.png"
ALT="$A^k$"></SPAN>,
<!-- MATH
$A^k_F = (\bar{a}_{ij}^k)$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="86" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="87" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img42.png"
ALT="$A^k_F = (\bar{a}_{ij}^k)$"></SPAN> is the filtered matrix defined as
</BIG></BIG></BIG>
@ -344,7 +344,7 @@ a_{ij}^k &amp; \m...
</TABLE>
<BR CLEAR="ALL"></DIV><P></P><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">
and <SPAN CLASS="MATH"><IMG
WIDTH="24" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="24" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img44.png"
ALT="$\omega^k$"></SPAN> is an approximation of <SPAN CLASS="MATH"><IMG
WIDTH="61" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
@ -373,14 +373,14 @@ of <SPAN CLASS="MATH"><IMG
SRC="img46.png"
ALT="$\rho^k$"></SPAN>. Note that for systems coming from uniformly elliptic
problems, filtering the matrix <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img41.png"
ALT="$A^k$"></SPAN> has little or no effect, and
<SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img41.png"
ALT="$A^k$"></SPAN> can be used instead of <SPAN CLASS="MATH"><IMG
WIDTH="28" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="29" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img49.png"
ALT="$A^k_F$"></SPAN>. The latter choice is the default in MLD2P4.
</BIG></BIG></BIG>

@ -68,7 +68,7 @@ the beginning of the current iteration.
</BIG></BIG></BIG>
<P>
<BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">In the AS methods, the index space <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img9.png"
ALT="$\Omega^k$"></SPAN> is divided into <SPAN CLASS="MATH"><IMG
WIDTH="28" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
@ -78,11 +78,11 @@ subsets <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img51.png"
ALT="$\Omega^k_i$"></SPAN> of size <SPAN CLASS="MATH"><IMG
WIDTH="31" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
WIDTH="32" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
SRC="img52.png"
ALT="$n_{k,i}$"></SPAN>, possibly
overlapping. For each <SPAN CLASS="MATH"><IMG
WIDTH="10" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="11" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img30.png"
ALT="$i$"></SPAN> we consider the restriction
operator <!-- MATH
@ -93,13 +93,13 @@ operator <!-- MATH
SRC="img53.png"
ALT="$R_i^k \in \mathbb{R}^{n_{k,i} \times n_k}$"></SPAN>
that maps a vector <SPAN CLASS="MATH"><IMG
WIDTH="23" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="23" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img54.png"
ALT="$x^k$"></SPAN> to the vector <SPAN CLASS="MATH"><IMG
WIDTH="22" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img55.png"
ALT="$x_i^k$"></SPAN> made of the components of <SPAN CLASS="MATH"><IMG
WIDTH="23" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="23" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img54.png"
ALT="$x^k$"></SPAN>
with indices in <SPAN CLASS="MATH"><IMG
@ -120,7 +120,7 @@ with indices in <SPAN CLASS="MATH"><IMG
WIDTH="113" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img57.png"
ALT="$A_i^k=R_i^kA^kP_i^k$"></SPAN>, which is the restriction of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="26" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img41.png"
ALT="$A^k$"></SPAN> to the index
space <SPAN CLASS="MATH"><IMG
@ -172,7 +172,7 @@ involves
SRC="img62.png"
ALT="$\Omega_i^k$"></SPAN> and of the corresponding
operators <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="26" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img63.png"
ALT="$R_i^k$"></SPAN> (and <SPAN CLASS="MATH"><IMG
WIDTH="26" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
@ -205,13 +205,13 @@ multilevel application phase, requires
</BIG></BIG></BIG>
<UL>
<LI>the restriction of <SPAN CLASS="MATH"><IMG
WIDTH="25" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="25" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img67.png"
ALT="$w^k$"></SPAN> to the subspaces <!-- MATH
$\mathbb{R}^{n_{k,i}}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="41" HEIGHT="19" ALIGN="BOTTOM" BORDER="0"
WIDTH="41" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img68.png"
ALT="$\mathbb{R}^{n_{k,i}}$"></SPAN>,
i.e. <!-- MATH

@ -83,14 +83,14 @@ i.e.,
matrix data structure;
</LI>
<LI>the arrays containing the vectors <SPAN CLASS="MATH"><IMG
WIDTH="14" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="14" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img72.png"
ALT="$v$"></SPAN> and <SPAN CLASS="MATH"><IMG
WIDTH="17" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img73.png"
ALT="$w$"></SPAN> involved in
the preconditioner application <SPAN CLASS="MATH"><IMG
WIDTH="81" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="82" HEIGHT="21" ALIGN="BOTTOM" BORDER="0"
SRC="img23.png"
ALT="$w=B^{-1}v$"></SPAN> must be of type
<code>psb_</code><SPAN CLASS="textit">x</SPAN><code>vect_type</code> with <SPAN CLASS="textit">x</SPAN> =

@ -326,10 +326,10 @@ Parameters defining the aggregation algorithm.
$\lfloor 40 \sqrt[3]{n} \rfloor$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="63" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
WIDTH="64" HEIGHT="38" ALIGN="MIDDLE" BORDER="0"
SRC="img76.png"
ALT="$\lfloor 40 \sqrt[3]{n} \rfloor$"></SPAN>, where <SPAN CLASS="MATH"><IMG
WIDTH="14" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="15" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img77.png"
ALT="$n$"></SPAN> is the dimension
of the matrix at the finest level</TD>
@ -376,7 +376,7 @@ Currently, only the
<code>SYMDEC</code> option applies decoupled
aggregation to the sparsity pattern
of <SPAN CLASS="MATH"><IMG
WIDTH="62" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="62" HEIGHT="40" ALIGN="MIDDLE" BORDER="0"
SRC="img79.png"
ALT="$A+A^T$"></SPAN>.</TD>
</TR>
@ -449,12 +449,12 @@ Parameters defining the aggregation algorithm (continued).
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=71>Any&nbsp;real
<P>
number&nbsp;<SPAN CLASS="MATH"><IMG
WIDTH="56" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
WIDTH="56" HEIGHT="36" ALIGN="MIDDLE" BORDER="0"
SRC="img80.png"
ALT="$\in [0, 1]$"></SPAN></TD>
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=65>0.01</TD>
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=187>The threshold <SPAN CLASS="MATH"><IMG
WIDTH="13" HEIGHT="20" ALIGN="BOTTOM" BORDER="0"
WIDTH="13" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img81.png"
ALT="$\theta$"></SPAN> in the aggregation algorithm,
see (<A HREF="node14.html#eq:strongly_coup">3</A>) in Section&nbsp;<A HREF="node14.html#sec:aggregation">4.2</A>.
@ -643,7 +643,7 @@ number <SPAN CLASS="MATH"><IMG
ALT="$\ge 0$"></SPAN></TD>
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=43>0</TD>
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=213>Drop tolerance <SPAN CLASS="MATH"><IMG
WIDTH="10" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="11" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img85.png"
ALT="$t$"></SPAN> in the ILU(<SPAN CLASS="MATH"><IMG
WIDTH="27" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
@ -866,7 +866,7 @@ Parameters defining the smoother or the details of the one-level preconditioner
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=62><SMALL CLASS="SMALL"> 0
</SMALL></TD>
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=201><SMALL CLASS="SMALL"> Drop tolerance <SPAN CLASS="MATH"><IMG
WIDTH="10" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="11" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img85.png"
ALT="$t$"></SPAN> in the ILU(<SPAN CLASS="MATH"><IMG
WIDTH="27" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"

@ -62,7 +62,7 @@ This method computes <!-- MATH
$y = op(B^{-1})\, x$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="113" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
WIDTH="113" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img86.png"
ALT="$y = op(B^{-1})\, x$"></SPAN>, where <SPAN CLASS="MATH"><IMG
WIDTH="19" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
@ -91,7 +91,7 @@ and hence it is completely transparent to the user.
<TR><TD ALIGN="LEFT" VALIGN="TOP" WIDTH=34><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">
</BIG></BIG></BIG></TD>
<TD ALIGN="LEFT" VALIGN="TOP" WIDTH=340><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE"> The local part of the vector <SPAN CLASS="MATH"><IMG
WIDTH="14" HEIGHT="16" ALIGN="BOTTOM" BORDER="0"
WIDTH="15" HEIGHT="18" ALIGN="BOTTOM" BORDER="0"
SRC="img88.png"
ALT="$x$"></SPAN>. Note that <SPAN CLASS="textit">type</SPAN> and
<SPAN CLASS="textit">kind_parameter</SPAN> must be chosen according
@ -137,28 +137,28 @@ and hence it is completely transparent to the user.
$op(B^{-1}) = B^{-1}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="123" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
WIDTH="123" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img90.png"
ALT="$op(B^{-1}) = B^{-1}$"></SPAN>;
if <code>trans</code> = <code>'T','t'</code> then <!-- MATH
$op(B^{-1}) = B^{-T}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="125" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="126" HEIGHT="40" ALIGN="MIDDLE" BORDER="0"
SRC="img91.png"
ALT="$op(B^{-1}) = B^{-T}$"></SPAN>
(transpose of <SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
WIDTH="44" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img92.png"
ALT="$B^{-1})$"></SPAN>; if <code>trans</code> = <code>'C','c'</code> then <!-- MATH
$op(B^{-1}) = B^{-C}$
-->
<SPAN CLASS="MATH"><IMG
WIDTH="126" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
WIDTH="126" HEIGHT="40" ALIGN="MIDDLE" BORDER="0"
SRC="img93.png"
ALT="$op(B^{-1}) = B^{-C}$"></SPAN>
(conjugate transpose of <SPAN CLASS="MATH"><IMG
WIDTH="43" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
WIDTH="44" HEIGHT="39" ALIGN="MIDDLE" BORDER="0"
SRC="img92.png"
ALT="$B^{-1})$"></SPAN>.</BIG></BIG></BIG></TD>
</TR>

@ -82,7 +82,7 @@ Ax=b,
</TABLE>
<BR CLEAR="ALL"></DIV><P></P><BIG CLASS="LARGE"><BIG CLASS="LARGE"><BIG CLASS="LARGE">
where <SPAN CLASS="MATH"><IMG
WIDTH="18" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
WIDTH="17" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
SRC="img3.png"
ALT="$A$"></SPAN> is a square, real or complex, sparse matrix.
The name of the package comes from its original implementation, containing

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