[mod] High performance linear algebra ~~ Added sparse matrix/vector support and boost of AX=B solve

Compute the `L * D * L^T` factorization of a real symmetric positive definite tridiagonal matrix `A`.

LAPACK routines.

Perform a series of row interchanges on an input matrix.

Copy all or part of a matrix A to another matrix B.

Convert a matrix from row-major layout to column-major layout or vice versa.

Determine double-precision floating-point machine parameters.

LAPACK auxiliary routine to apply a plane rotation with real cosine and complex sine.

Set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values.

Copy all or part of a matrix A to another matrix B.

Compute the `L * D * L^T` factorization of a real symmetric positive definite tridiagonal matrix `A`.

LAPACK auxiliary routine to apply a plane rotation with real cosine and complex sine.

Perform a series of row interchanges on an input matrix.

Convert input general matrix from row-major to column-major layout or vice versa.

Conjugate each element in a double-precision complex floating-point vector.

Copy all or part of a matrix A to another matrix B.

Set the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values.

Conjugate each element in a single-precision complex floating-point vector.

Return an updated sum of squares represented in scaled form.

Copy all or part of a matrix A to another matrix B.