\texttt{ParameterAcceptor::initialize}, greatly simplifying
dealing with parameters in user codes.
-\item New caching mechanism for expensive grid computations: we introduced a new
+\item A new caching mechanism for expensive grid computations: this version introduces a new
class \texttt{GridTools::Cache} that caches computationally intensive
information about a \texttt{Triangulation}.
This class allows the user to query some of the data structures constructed
using functions in the \texttt{GridTools} namespace. This data is then
computed only once, and
-then cached inside this class for faster access whenever the triangulation has
+cached inside this class for faster access whenever the triangulation has
not changed. The cache is marked for update by the \texttt{Triangulation} itself
-using signals.
+using signals so that data is properly invalidated upon mesh
+refinement and coarsening.
Some of the methods in \texttt{GridTools} already use this cache to
speed up repeated calls to the same expensive methods.
demonstrates this technique based on the Trilinos Sacado \cite{Bartlett2006a} package, but
the functionality was not available pervasively throughout
deal.II.
-This has changed with release 9.0 where support is given for differentiation
+This has changed with release 9.0 where support for differentiation is
+now available
using a selection of ``white-listed'' libraries (namely ADOL-C \citep{Griewank1996a}
and Sacado) and a subset of their supported number types. Currently,
we offer support for the following cases:
\item Sacado nested reverse and dynamic forward (twice differentiable).
\end{itemize}
In practice, this support means that these ADOL-C and Sacado data
-types can be used in the \texttt{FEValues}, \texttt{FEValuesViews},
+types can be used as the underlying ``scalar'' in the \texttt{FEValues}, \texttt{FEValuesViews},
\texttt{Tensor}, \texttt{SymmetricTensor},
and related classes that are generally used to assemble linear systems
and right hand sides.
Given the updated capabilities of the library, there is now a dedicated module
that presents the AD compatibility and capabilities of the \dealii libraries.
-Furthermore, the use of Sacado is now demonstrated in a much more simplified
+Furthermore, the use of Sacado is demonstrated in a much more simplified
and transparent manner in a modernized version of an existing ``code gallery''
example \cite{Pelteret2016a}.
\dealii now has interfaces to SUNDIALS's ARKode, IDA, and KINSOL sub-packages.
ARKode is a solver library that provides adaptive-step time
integration. IDA is a package for the solution of differential-algebraic
- equations systems in the form $F(t,y,y')=0$. KINSOL is solver for nonlinear
+ equations systems in the form $F(t,y,y')=0$. KINSOL is a solver for nonlinear
algebraic systems.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\texttt{Mapping::clone()}) now return \texttt{std::unique\_ptr}s instead of
C-style raw pointers. Indeed, nearly all interfaces throughout the library that return a pointer
now return either a \texttt{std::shared\_ptr} or a \texttt{std::unique\_ptr},
-thereby clarifying object ownership responsibilities and avoiding memory leaks.
+thereby clarifying object ownership and avoiding memory leaks.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
This release of \dealii adds support for GPUs both for matrix-based and
matrix-free applications. For matrix-based applications, we rely on
-cuSPARSE\cite{cusparse} and cuSOLVER\cite{cusolver} for operations on sparse
+cuSPARSE \cite{cusparse} and cuSOLVER \cite{cusolver} for operations on sparse
matrices such as matrix-vector multiplication and for direct solvers. We have
introduced a new type of sparse matrix, \texttt{CUDAWrappers::SparseMatrix},
which moves onto the device a \dealii \texttt{SparseMatrix} and changes the
format of the underlying data to the appropriate CSR format used by cuSPARSE. We
also have added wrappers for Cholesky and LU factorizations provided by
-cuSOLVER. In practice, a user would assemble the matrix associated to the system
-on the host and then move the matrix to the device. At this point, the system
+cuSOLVER. In practice, a user would assemble the system matrix and
+right hand side vector
+on the host and then move them to the device. At this point, the
+linear system
would be solved on the device and the solution would be moved back to the host.
We also have some support for matrix-free computation on a GPU. For now, the
-evaluation of the operator is limited to mesh without hanging-nodes.
+evaluation of the operator is limited to meshes without hanging nodes.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
The tutorial program \texttt{step-60} shows how to perform computations on
non-matching grids, and it presents advanced manipulation of
-\texttt{ParameterHandler} objects, exploiting the new \texttt{ParameterAccessor}
+\texttt{ParameterHandler} objects using the new \texttt{ParameterAccessor}
and \texttt{ParameterAccessorProxy} classes. \texttt{step-60} solves a Poisson
problem on a domain $\Omega$, subject to equality constraints defined on an
embedded domain $\Gamma$. The embedded domain can be of co-dimension one or
In order to enforce correctly the constraints, a non-matching coupling matrix
needs to be constructed. This is achieved using the new
\texttt{NonMatching::create\_coupling\_sparsity\_pattern} and
-\texttt{NonMatching::create\_coupling\_mass\_matrix}, that exploit some new
+\texttt{NonMatching::create\_coupling\_mass\_matrix} functions that exploit new
functionality in the \texttt{GridTools} namespace.
\dealii has a separate ``code gallery'' that
projects / release-papers.git / commitdiff