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Trilinos/Tpetra: Next-generation distributed linear algebra


Tpetra implements linear algebra objects, such as sparse matrices and dense vectors. Tpetra is "hybrid parallel," meaning that it uses up to two levels of parallelism:

We say "distributed linear algebra" because Tpetra objects may be distributed over one or more parallel MPI processes. The shared-memory programming models that Tpetra may use within a process include

Tpetra differs from Epetra, Trilinos' previous distributed linear algebra package, in the following ways:

1. Tpetra has native support for solving very large problems (with over 2 billion unknowns).

2. Tpetra lets you construct matrices and vectors with different kinds of data, such as floating-point types of different precision, or complex-valued types. Our goal is for Tpetra objects to be able to contain any type of data that implements a minimal compile-time interface. Epetra objects only support double-precision floating-point data (of type double).

3. Tpetra can exploit many different kinds of hybrid parallelism, and most of its kernels do so natively. Epetra only supports OpenMP shared-memory parallelism for a few kernels. Tpetra also has optimizations for shared-memory parallel systems with nonuniform memory access (NUMA). All effort in supporting future node-level computer architectures will go into Tpetra.

Overview of Tpetra

Templated Types in Tpetra

All of all classes in Tpetra utilize templates, which allows the user to specify any type they want. In some cases, the choice of data type allows increased functionality. For example, 64-bit ordinals allow for problem sizes to break the 2 billion element barrier present in Epetra, whereas complex scalar types allow the native description and solution of complex-valued problems.

Most of the classes in Tpetra are templated according to the data types which constitute the class. These are the following:

The Tpetra::Distributor class is unique in that it is not parametrized by any templated types. However, the class includes some templated member functions. The Tpetra::Distributor::createFromRecvs() method is templated on the ordinal type used to encode IDs, while Tpetra::Distributor::doPosts() and the other post methods are templated on Packet, the data type being communicated by a particular invocation of the Tpetra::Distributor. This allows a single Tpetra::Distributor object (describing a particular communication pattern) to be used to communicate values of different type.

Tpetra Classes

Tpetra contains a number of classes. The primary parallel classes, employed by most users, are:

Trilinos and Tpetra

Tpetra can be used mostly as a stand-alone package, with explicit dependencies on Teuchos and Kokkos. There are adapters allowing the use of Tpetra operators and multivectors in both the Belos linear solver package and the Anasazi eigensolver package.

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