Stratimikos Version of the Day
|TsqrAdaptor (const MV &mv, const Teuchos::RCP< const Teuchos::ParameterList > &plist)|
|void||factorExplicit (MV &A, MV &Q, dense_matrix_type &R)|
|Compute QR factorization [Q,R] = qr(A,0) |
|int||revealRank (MV &Q, dense_matrix_type &R, const magnitude_type &tol)|
|Rank-revealing decomposition. |
|static Teuchos::RCP< const |
|Default parameters. |
Stub adaptor from Thyra::MultiVectorBase to TSQR.
TSQR (Tall Skinny QR factorization) is an orthogonalization kernel that is as accurate as Householder QR, yet requires only messages between $P$ MPI processes, independently of the number of columns in the multivector.
TSQR works independently of the particular multivector implementation, and interfaces to the latter via an adaptor class. Thyra::TsqrAdaptor is the adaptor class for Thyra::MultiVectorBase. It templates on the MultiVector (MV) type so that it can pick up that class' typedefs. In particular, TSQR chooses its intranode implementation based on the Kokkos Node type of the multivector.
|Thyra::TsqrAdaptor< Scalar >::TsqrAdaptor||(||const MV &||mv,|
|const Teuchos::RCP< const Teuchos::ParameterList > &||plist|
|mv||[in] Multivector object, used only to access the underlying communicator object (in this case, Teuchos::Comm<int>, accessed via the Tpetra::Map belonging to the multivector). All multivector objects with which this Adaptor works must use the same map and communicator.|
|plist||[in] List of parameters for configuring TSQR. The specific parameter keys that are read depend on the TSQR implementation. "cacheBlockSize" (cache block size per core, in bytes) tends to be defined for all of the non-GPU implementations. For details, check the specific NodeTsqrFactory implementation.|
|static Teuchos::RCP<const Teuchos::ParameterList> Thyra::TsqrAdaptor< Scalar >::getDefaultParameters||(||)||
Return default parameters for the TSQR variant used by Epetra.
|void Thyra::TsqrAdaptor< Scalar >::factorExplicit||(||MV &||A,|
|int Thyra::TsqrAdaptor< Scalar >::revealRank||(||MV &||Q,|
|const magnitude_type &||tol|
Using the R factor and explicit Q factor from factorExplicit(), compute the singular value decomposition (SVD) of R ( ). If R is full rank (with respect to the given relative tolerance tol), don't change Q or R. Otherwise, compute and in place (the latter may be no longer upper triangular).
|Q||[in/out] On input: explicit Q factor computed by factorExplicit(). (Must be an orthogonal resp. unitary matrix.) On output: If R is of full numerical rank with respect to the tolerance tol, Q is unmodified. Otherwise, Q is updated so that the first rank columns of Q are a basis for the column space of A (the original matrix whose QR factorization was computed by factorExplicit()). The remaining columns of Q are a basis for the null space of A.|
|R||[in/out] On input: ncols by ncols upper triangular matrix with leading dimension ldr >= ncols. On output: if input is full rank, R is unchanged on output. Otherwise, if is the SVD of R, on output R is overwritten with $ V^*$. This is also an ncols by ncols matrix, but may not necessarily be upper triangular.|
|tol||[in] Relative tolerance for computing the numerical rank of the matrix R.|