Modules List

Here is a list of all documented modules with brief descriptions:

[detail level 12]

▼Mblas	A module providing explicit interfaces to BLAS routines
Cddot
Cdgbmv
Cdgemm
Cdgemv
Cdscal
Cdtrsm
Cdtrsv
Czdscal
Czgbmv
Czgemm
Czgemv
Czscal
Cztrsm
Cztrsv
▼Mlinalg	Provides a set of common linear algebra routines
Cband_diag_mtx_mult	Multiplies a banded matrix, A, with a diagonal matrix, B, such that A = alpha * A * B, or A = alpha * B * A
Cband_mtx_mult	Multiplies a banded matrix, A, by a vector x such that alpha * op(A) * x + beta * y = y
Cband_mtx_to_full_mtx	Converts a banded matrix stored in dense form to a full matrix
Cbanded_to_dense	Converts a banded matrix to a dense matrix
Ccholesky_factor	Computes the Cholesky factorization of a symmetric, positive definite matrix
Ccholesky_rank1_downdate	Computes the rank 1 downdate to a Cholesky factored matrix (upper triangular)
Ccholesky_rank1_update	Computes the rank 1 update to a Cholesky factored matrix (upper triangular)
Ccsr_matrix	A sparse matrix stored in compressed sparse row (CSR) format
Cdense_to_banded	Converts a dense matrix to a banded matrix
Cdet	Computes the determinant of a square matrix
Cdiag_mtx_mult	Multiplies a diagonal matrix with another matrix or array
Ceigen	Computes the eigenvalues, and optionally the eigenvectors, of a matrix
Cextract_diagonal	Extracts the diagonal of a matrix
Cform_lq	Forms the orthogonal matrix Q from the elementary reflectors returned by the LQ factorization algorithm
Cform_lu	Extracts the L and U matrices from the condensed [L\U] storage format used by the lu_factor
Cform_qr	Forms the full M-by-M orthogonal matrix Q from the elementary reflectors returned by the base QR factorization algorithm
Clq_factor	Computes the LQ factorization of an M-by-N matrix
Clu_factor	Computes the LU factorization of an M-by-N matrix
Cmatmul	Performs sparse matrix multiplication C = A * B
Cmsr_matrix	A sparse matrix stored in modified sparse row format. This format is convenient for situations where the diagonal is fully populated
Cmtx_inverse	Computes the inverse of a square matrix
Cmtx_mult	Performs the matrix operation: \( C = \alpha op(A) op(B) + \beta C \)
Cmtx_pinverse	Computes the Moore-Penrose pseudo-inverse of a M-by-N matrix using the singular value decomposition of the matrix
Cmtx_rank	Computes the rank of a matrix
Cmult_lq	Multiplies a general matrix by the orthogonal matrix Q from a LQ factorization
Cmult_qr	Multiplies a general matrix by the orthogonal matrix Q from a QR factorization
Cmult_rz	Multiplies a general matrix by the orthogonal matrix Z from an RZ factorization
Cnonzero_count	Determines the number of nonzero entries in a sparse matrix
Coperator(*)	Multiplies a sparse matrix and a scalar
Coperator(+)	Adds two sparse matrices
Coperator(-)	Subtracts two sparse matrices
Coperator(/)	Multiplies a sparse matrix by a scalar
Cpgmres_solver	A preconditioned GMRES solver
Cqr_factor	Computes the QR factorization of an M-by-N matrix
Cqr_rank1_update	Computes the rank 1 update to an M-by-N QR factored matrix A (M >= N) where \( A = Q R \), and \( A1 = A + U V^T \) such that \( A1 = Q1 R1 \). In the event \( V \) is complex-valued, \( V^H \) is computed instead of \( V^T \)
Crank1_update	Performs the rank-1 update to matrix A such that: \( A = \alpha X Y^T + A \), where \( A \) is an M-by-N matrix, \( \alpha \)is a scalar, \( X \) is an M-element array, and \( Y \) is an N-element array. In the event that \( Y \) is complex, \( Y^H \) is used instead of \( Y^T \)
Crecip_mult_array	Multiplies a vector by the reciprocal of a real scalar
Crz_factor	Factors an upper trapezoidal matrix by means of orthogonal transformations such that \( A = R Z = (R 0) Z \). Z is an orthogonal matrix of dimension N-by-N, and R is an M-by-M upper triangular matrix
Csize	Determines the size of the requested dimension of the supplied sparse matrix
Csolve_cholesky	Solves a system of Cholesky factored equations
Csolve_least_squares	Solves the overdetermined or underdetermined system \( A X = B \) of M equations of N unknowns. Notice, it is assumed that matrix A has full rank
Csolve_least_squares_full	Solves the overdetermined or underdetermined system \( A X = B \) of M equations of N unknowns, but uses a full orthogonal factorization of the system
Csolve_least_squares_svd	Solves the overdetermined or underdetermined system \( A X = B \) of M equations of N unknowns using a singular value decomposition of matrix A
Csolve_lq	Solves a system of M LQ-factored equations of N unknowns. N must be greater than or equal to M
Csolve_lu	Solves a system of LU-factored equations
Csolve_qr	Solves a system of M QR-factored equations of N unknowns
Csolve_triangular_system	Solves a triangular system of equations
Csort	Sorts an array
Csparse_direct_solve	Provides a direct solution to a square, sparse system
Csvd	Computes the singular value decomposition of a matrix A. The SVD is defined as: \( A = U S V^T \), where \( U \) is an M-by-M orthogonal matrix, \( S \) is an M-by-N diagonal matrix, and \( V \) is an N-by-N orthogonal matrix. In the event that \( V \) is complex valued, \( V^H \) is computed instead of \( V^T \)
Cswap	Swaps the contents of two arrays
Ctrace	Computes the trace of a matrix (the sum of the main diagonal elements)
Ctranspose	Provides the transpose of a sparse matrix
Ctri_mtx_mult	Computes the triangular matrix operation: \( B = \alpha A^T A + \beta B \), or \( B = \alpha A A^T + \beta B \), where A is a triangular matrix
▼Mqrupdate	A module providing explicit interfaces for the QRUPDATE library
Cdch1dn
Cdch1up
Cdqr1up
Czch1dn
Czch1up
Czqr1up
▼Msparskit	An interface to the SPARSKIT library available at https://www-users.cse.umn.edu/~saad/software/SPARSKIT/
Camub	Computes the matrix product: C = A * B
Caplb	Computes the matrix sum: C = A + B, where the matrices are given in CSR format
Caplsb	Computes the matrix sum: C = A + s * B, where the matrices are given in CSR format
Cbndcsr	Converts the LINPACK, BLAS, LAPACK banded matrix format into a CSR format
Cclncsr	@breif Cleans up a CSR matrix
Ccoocsr	Converte a matrix stored in coordinate format to CSR format
Ccsort	Sorces the elements of a CSR matrix in increasing order of their column indices within each row
Ccsrcsc2	Converts a CSR matrix into a CSC matrix (transposition)
Ccsrmsr	Converts a CSR matrix to an MSR matrix
Cgetdia	Extracts the diagonal from a matrix
Cgetelm	Gets element A(i,j) of matrix A for any pair (i,j)
Cilud	Computes the incomplete LU factorization of a sparse matrix in CSR format with standard dropping strategy
Ciludp	Computes the incomplete LU factorization of a sparse matrix in CSR format with standard dropping strategy
Cilut	Computes the incomplete LU factorization of a sparse matrix in CSR format using a dual truncation mechanism
Cilutp	Computes the incomplete LU factorization of a sparse matrix in CSR format using a dual truncation mechanism and pivoting
Clusol	Solves the LU-factored system (LU) x = y
Cmsrcsr	Converts and MSR matrix to a CSR matrix
Cpgmres	An ILUT preconditioned GMRES algorithm. This routine utilizes the L and U matrices generated by the ILUT routine to precondition the GMRES algorithm. The stopping criteria utilized is based simply on reducing the residual norm to the requested tolerance