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Merged vect-state branch. 
Now need to:
1. Update MLD
2. Fix documentation
3. Take out older Krylov interfaces.
This commit is contained in:
Salvatore Filippone
2011-10-24 11:30:02 +00:00
parent 81ceebf074
commit afa7aafb52
538 changed files with 61478 additions and 28996 deletions
+195 -38
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@@ -7,8 +7,8 @@ original version by: Nikos Drakos, CBLU, University of Leeds
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<H2><A NAME="SECTION00043000000000000000"></A>
<A NAME="sec:prec"></A>
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<BR>
Preconditioner data structure
Dense Vector Data Structure
</H2>
Our base library offers support for simple well known preconditioners
like Diagonal Scaling or Block Jacobi with incomplete
factorization ILU(0).
The vdata<TT>psb_vect_type</TT> data structure
contains all information about local portion of the sparse matrix and
its storage mode. Most of these fields are set by the tools
routines when inserting a new sparse matrix; the user needs only
choose, if he/she so whishes, a specific matrix storage mode.
<BR><DL>
<DT><STRONG><B>aspk</B></STRONG></DT>
<DD>Contains values of the local distributed sparse
matrix.
<BR>
Specified as: an allocatable array of rank one of type corresponding
to matrix entries type.
</DD>
<DT><STRONG><B>ia1</B></STRONG></DT>
<DD>Holds integer information on distributed sparse
matrix. Actual information will depend on data format used.
<BR>
Specified as: an allocatable integer array of rank one.
</DD>
<DT><STRONG><B>ia2</B></STRONG></DT>
<DD>Holds integer information on distributed sparse
matrix. Actual information will depend on data format used.
<BR>
Specified as: an allocatable integer array of rank one.
</DD>
<DT><STRONG><B>infoa</B></STRONG></DT>
<DD>On entry can hold auxiliary information on distributed sparse
matrix. Actual information will depend on data format used.
<BR>
Specified as: an integer array of length <code>psb_ifasize_</code>.
</DD>
<DT><STRONG><B>fida</B></STRONG></DT>
<DD>Defines the format of the distributed sparse matrix.
<BR>
Specified as: a string of length 5
</DD>
<DT><STRONG><B>descra</B></STRONG></DT>
<DD>Describe the characteristic of the distributed sparse matrix.
<BR>
Specified as: array of character of length 9.
</DD>
<DT><STRONG><B>pl</B></STRONG></DT>
<DD>Specifies the local row permutation of distributed sparse
matrix. If pl(1) is equal to 0, then there isn't row permutation.
<BR>
Specified as: an allocatable integer array of dimension equal to number of local row (matrix_data[psb_n_row_])
</DD>
<DT><STRONG><B>pr</B></STRONG></DT>
<DD>Specifies the local column permutation of distributed sparse
matrix. If PR(1) is equal to 0, then there isn't columnm permutation.
<BR>
Specified as: an allocatable integer array of dimension equal to number of
local row (matrix_data[psb_n_col_])
</DD>
<DT><STRONG><B>m</B></STRONG></DT>
<DD>Number of rows; if row indices are stored explicitly,
as in Coordinate Storage, should be greater than or equal to the
maximum row index actually present in the sparse matrix.
Specified as: integer variable.
</DD>
<DT><STRONG><B>k</B></STRONG></DT>
<DD>Number of columns; if column indices are stored explicitly,
as in Coordinate Storage or Compressed Sparse Rows, should be greater
than or equal to the maximum column index actually present in the sparse matrix.
Specified as: integer variable.
</DD>
</DL>
The Fortran&nbsp;95 interface for distributed sparse matrices containing
double precision real entries is defined as shown in
figure&nbsp;<A HREF="#fig:spmattype">5</A>. The definitions for single precision and
complex data are identical except for the <code>real</code> declaration and
for the kind type parameter.
<P>
A preconditioner is held in the precdata<TT> psb_prec_type</TT> data structure reported in
figure&nbsp;<A HREF="#fig:prectype">5</A>. The <code>psb_prec_type</code>
data type may contain a simple preconditioning matrix with the
associated communication descriptor.The values contained in
the <code>iprcparm</code> and <code>rprcparm</code> define tha type of
preconditioner along with all the parameters related to it; thus,
<code>iprcparm</code> and <code>rprcparm</code> define how the other records have
to be interpreted. This data structure is the basis of more complex
preconditioning strategies, which are the subject of further
research.
<DIV ALIGN="CENTER"><A NAME="fig:prectype"></A><A NAME="626"></A>
<DIV ALIGN="CENTER"><A NAME="fig:spmattype"></A><A NAME="672"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 5:</STRONG>
The PSBLAS defined data type that contains a preconditioner.</CAPTION>
<TR><TD><FONT SIZE="-1"> <BR>
The PSBLAS defined data type that
contains a sparse matrix.</CAPTION>
<TR><TD>
<BR>
</FONT>
<DIV ALIGN="CENTER"><FONT SIZE="-1"><!-- MATH
<DIV ALIGN="CENTER">
<!-- MATH
$\fbox{\TheSbox}$
-->
<IMG
WIDTH="536" HEIGHT="218" ALIGN="MIDDLE" BORDER="0"
WIDTH="535" HEIGHT="218" ALIGN="MIDDLE" BORDER="0"
SRC="img20.png"
ALT="\fbox{\TheSbox}"></FONT></DIV><FONT SIZE="-1">
</FONT></TD></TR>
ALT="\fbox{\TheSbox}">
</DIV></TD></TR>
</TABLE>
</DIV>
<P>
The following two cases are among the most commonly used:
<DL>
<DT><STRONG>fida=``CSR''</STRONG></DT>
<DD>Compressed storage by rows. In this case the
following should hold:
<OL>
<LI><code>ia2(i)</code> contains the index of the first element of row
<code>i</code>; the last element of the sparse matrix is thus stored at
index <IMG
WIDTH="107" HEIGHT="32" ALIGN="MIDDLE" BORDER="0"
SRC="img22.png"
ALT="$ia2(m+1)-1$">. It should contain <code>m+1</code> entries in
nondecreasing order (strictly increasing, if there are no empty rows).
</LI>
<LI><code>ia1(j)</code> contains the column index and <code>aspk(j)</code>
contains the corresponding coefficient value, for all <!-- MATH
$ia2(1) \le j
\le ia2(m+1)-1$
-->
<IMG
WIDTH="200" HEIGHT="32" ALIGN="MIDDLE" BORDER="0"
SRC="img23.png"
ALT="$ia2(1) \le j
\le ia2(m+1)-1$">.
</LI>
</OL>
</DD>
<DT><STRONG>fida=``COO''</STRONG></DT>
<DD>Coordinate storage. In this case the following
should hold:
<OL>
<LI><code>infoa(1)</code> contains the number of nonzero elements in the
matrix;
</LI>
<LI>For all <!-- MATH
$1 \le j \le infoa(1)$
-->
<IMG
WIDTH="122" HEIGHT="32" ALIGN="MIDDLE" BORDER="0"
SRC="img24.png"
ALT="$1 \le j \le infoa(1)$">, the coefficient, row index and
column index are stored into <code>apsk(j)</code>, <code>ia1(j)</code> and
<code>ia2(j)</code> respectively.
</LI>
</OL>
</DD>
</DL>
A sparse matrix has an associated state, which can take the following
values:
<DL>
<DT><STRONG>Build:</STRONG></DT>
<DD>State entered after the first allocation, and before the
first assembly; in this state it is possible to add nonzero entries.
</DD>
<DT><STRONG>Assembled:</STRONG></DT>
<DD>State entered after the assembly; computations using
the sparse matrix, such as matrix-vector products, are only possible
in this state;
</DD>
<DT><STRONG>Update:</STRONG></DT>
<DD>State entered after a reinitalization; this is used to
handle applications in which the same sparsity pattern is used
multiple times with different coefficients. In this state it is only
possible to enter coefficients for already existing nonzero entries.
</DD>
</DL>
<BR><HR>
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