Here is a list of all modules with brief descriptions:

Mla_blas	Precision-agnostic BLAS interface
Mla_blas_aux	BLAS helpers: character comparison, error reporting, index of maximum
Mla_blas_level1	BLAS level 1: vector operations
Mla_blas_level2_ban	BLAS level 2: banded matrix-vector operations
Mla_blas_level2_gen	BLAS level 2: general matrix-vector operations and rank updates
Mla_blas_level2_pac	BLAS level 2: packed and symmetric-banded matrix-vector operations
Mla_blas_level2_sym	BLAS level 2: symmetric matrix-vector operations
Mla_blas_level2_tri	BLAS level 2: triangular matrix-vector operations
Mla_blas_level3_gen	BLAS level 3: general and Hermitian matrix-matrix operations
Mla_blas_level3_sym	BLAS level 3: symmetric matrix-matrix operations
Mla_blas_level3_tri	BLAS level 3: triangular matrix-matrix operations
Mla_cholesky	Cholesky factorization of a matrix, based on LAPACK POTRF functions
Mla_constants	Supported kind parameters
Mla_constants_dp	64-bit BLAS/LAPACK constants
Mla_constants_qp	128-bit BLAS/LAPACK constants
Mla_constants_sp	32-bit BLAS/LAPACK constants
Mla_determinant	Determinant of a rectangular matrix
Mla_eig	Eigenvalues and Eigenvectors
Mla_eye	Identity and diagonal matrices, matrix trace and elementary matrix products
Mla_inverse	Inverse of a square matrix
Mla_lapack	Kind-agnostic LAPACK interface linking to internal or external implementations
Mla_lapack_aux	LAPACK helpers: environment enquiry, character decoding, index scans
Mla_lapack_auxiliary	LAPACK auxiliary: machine parameters, safe division, band scaling
Mla_lapack_blas_like_base	BLAS-like base: copy, precision conversion, random and packed storage
Mla_lapack_blas_like_l1	BLAS-like level 1: scaling, conjugation, sums of squares, sorting
Mla_lapack_blas_like_l2	BLAS-like level 2: matrix-vector products, scaling, rank updates
Mla_lapack_blas_like_l3	BLAS-like level 3: rank-k updates and solves in RFP storage
Mla_lapack_blas_like_mnorm	BLAS-like matrix norms
Mla_lapack_blas_like_scalar	BLAS-like scalar: complex division, Pythagorean sums, NaN tests
Mla_lapack_cosine_sine	Cosine-sine decomposition: bidiagonal block form, simultaneous bidiagonalization, row and column permutations
Mla_lapack_eigv_comp	Generalized nonsymmetric eigenproblem components: balancing, Hessenberg-triangular reduction, QZ iteration
Mla_lapack_eigv_comp2	Generalized nonsymmetric eigenproblem components: eigenvectors, block swaps, deflating subspaces, Sylvester solves
Mla_lapack_eigv_gen	Nonsymmetric eigenvalue, Schur and generalized Schur drivers
Mla_lapack_eigv_gen2	Nonsymmetric eigenproblem components: Schur factorization, eigenvectors, reordering and condition numbers
Mla_lapack_eigv_gen3	Nonsymmetric eigenproblem kernels: multishift QR and QZ sweeps with aggressive early deflation
Mla_lapack_eigv_gen_aux	Nonsymmetric eigenproblem helpers: 2-by-2 standardization, Sylvester solves, diagonal block swaps
Mla_lapack_eigv_gen_hess	Hessenberg reduction: balancing, back-transformation, orthogonal factor generation
Mla_lapack_eigv_svd_bidiag_dc	Bidiagonal singular values by divide and conquer, with its secular-equation and merge kernels
Mla_lapack_eigv_svd_drivers	SVD drivers: QR iteration and the rank-revealing preconditioned variant
Mla_lapack_eigv_svd_drivers2	SVD drivers: divide and conquer, Jacobi and preconditioned Jacobi
Mla_lapack_eigv_sym	Symmetric and Hermitian eigenvalue drivers: dense, packed, banded and generalized problems
Mla_lapack_eigv_sym_comp	Symmetric eigenproblem components: tridiagonal and band reductions, generalized to standard form
Mla_lapack_eigv_tridiag	Symmetric tridiagonal eigenvalues: divide and conquer, rank-one updates, implicit QL and QR
Mla_lapack_eigv_tridiag2	Symmetric tridiagonal eigenvalues: MRRR representation tree, bisection, eigenvector generation
Mla_lapack_eigv_tridiag3	Symmetric tridiagonal eigenvalue drivers: divide and conquer, MRRR, bisection and inverse iteration
Mla_lapack_givens_jacobi_rot	Givens and Jacobi plane rotations
Mla_lapack_householder_reflectors	Householder reflectors: generation, blocking, application
Mla_lapack_lsq	Least-squares drivers: QR, complete orthogonal, SVD and divide-and-conquer solutions
Mla_lapack_lsq_aux	Least-squares helpers: incremental condition estimation and divide-and-conquer back-substitution
Mla_lapack_lsq_constrained	Constrained least squares: equality constraints and the general Gauss-Markov model
Mla_lapack_orthogonal_factors_ql	LQ and QL factorizations: blocked, short-wide and triangular-pentagonal variants
Mla_lapack_orthogonal_factors_qr	QR and RQ factorizations: blocked, tall-skinny, pivoted and triangular-pentagonal variants
Mla_lapack_orthogonal_factors_rz	RZ factorization: trapezoidal reduction and its reflectors
Mla_lapack_others_sm	Extra-precise refinement helpers: condition numbers and pivot growth
Mla_lapack_solve_aux	Linear solve helpers: condition estimation, componentwise backward error
Mla_lapack_solve_chol	Cholesky drivers: positive definite, packed, banded and tridiagonal systems
Mla_lapack_solve_chol_comp	Cholesky components: factorization, solve, inverse, condition, equilibration
Mla_lapack_solve_ldl	Symmetric and Hermitian indefinite drivers
Mla_lapack_solve_ldl_comp	Symmetric indefinite components: Bunch-Kaufman factorization, solve, inverse
Mla_lapack_solve_ldl_comp2	Symmetric indefinite components: rook, Aasen and rank-k variants
Mla_lapack_solve_ldl_comp3	Hermitian indefinite components: Bunch-Kaufman factorization, solve, inverse
Mla_lapack_solve_ldl_comp4	Hermitian indefinite components: rook, Aasen and rank-k variants
Mla_lapack_solve_lu	LU drivers: general, banded and tridiagonal systems
Mla_lapack_solve_lu_comp	LU components: factorization, solve, inverse, condition, equilibration
Mla_lapack_solve_tri_comp	Triangular systems: solve, inverse, condition estimation, refinement
Mla_lapack_svd_bidiag_qr	Bidiagonal singular values: implicit QR sweep and the dqds algorithm
Mla_lapack_svd_comp	SVD components: bidiagonal reduction and its orthogonal factors, Jacobi sweeps, generalized SVD
Mla_lapack_svd_comp2	SVD components: bidiagonal reduction, 2-by-2 singular values, Jacobi generators
Mla_least_squares	Least squares solution interface
Mla_matrix_property_checks	Matrix property checks
Mla_norms	Matrix and Vector norms
Mla_pseudoinverse
Mla_qr	QR factorization of a matrix
Mla_schur
Mla_solve
Mla_state_type	State and error handling module for linear algebra routines
Mla_svd	Singular Value Decomposition
Mlinear_algebra