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Update documentation for release

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sfilippone
2025-12-23 11:21:53 +01:00
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docs/src/gettingstarted.tex
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@@ -94,7 +94,6 @@ Multilevel &\fortinline|'ML'| & V-cycle with one hybrid forward Gauss-
\label{tab:precinit}}
\end{center}
\end{table}
Note that the module \fortinline|amg_prec_mod|, containing the definition of the
preconditioner data type and the interfaces to the routines of AMG4PSBLAS,
must be used in any program calling such routines.
@@ -110,6 +109,12 @@ a standard discretization of basic scalar elliptic PDE problems. However,
this does not necessarily correspond to the shortest execution time
on parallel~computers.
\textbf{Remark 2.} Memory allocation on GPUs is a costly operation
implying a synchronization; therefore, it is convenient to preallocate
internal preconditioner workspace with the method
\verb|prec%allocate_wrk(info)| before invoking an iterative method,
and release it upon exit with \verb|prec%deallocate_wrk(info)|.
\subsection{Examples\label{sec:examples}}
@@ -140,7 +145,6 @@ for the real single precision and the complex, single and double
precision, versions are obtained with straightforward modifications of the previous
example (see Section~\ref{sec:userinterface} for details). If these versions are installed,
the corresponding codes are available in \verb|samples/simple/file|\-\verb|read|.
\begin{listing}[tbp]
\begin{center}
\begin{minipage}{.90\textwidth}
@@ -260,7 +264,6 @@ stop
\label{fig:ex1}}
\end{center}
\end{listing}
Different versions of the multilevel preconditioner can be obtained by changing
the default values of the preconditioner parameters. The code reported in
Figure~\ref{fig:ex2} shows how to set a V-cycle preconditioner
@@ -272,10 +275,15 @@ with block-Jacobi and set by~\fortinline|P%init|.
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 using the Coarsening based on Compatible Weighted Matching, aggregates of size at most $8$ and smoothed prolongators. It applies
Figure~\ref{fig:ex3} shows how to set a W-cycle preconditioner using
the Coarsening based on Compatible Weighted Matching, aggregates of
size at most $8$ and smoothed prolongators. It applies
2 hybrid Gauss-Seidel sweeps as pre- and post-smoother,
and solves the coarsest-level system with the parallel flexible Conjugate Gradient method (KRM) coupled with the block-Jacobi preconditioner having ILU(0) on the blocks. Default parameters are used for stopping criterion of the coarsest solver.
Note that, also in this case, specifying KRM as coarsest-level
and solves the coarsest-level system with the parallel flexible
Conjugate Gradient method (KRM) coupled with the block-Jacobi
preconditioner having ILU(0) on the blocks, with default parameters
used for the coarsest solver.
Note that specifying KRM as coarsest-level
solver implies that the coarsest-level matrix is distributed
among the processes.
%It is specified that the coarsest-level