# Module supernodal

## Expand description

Supernodal factorization module.

A supernodal factorization is one that processes the elements of the QR factors of the input matrix by blocks, rather than by single elements. This is more efficient if the QR factors are somewhat dense.

## Structs§

- QR factors containing both the symbolic and numeric representations.
- Symbolic structure of the Householder reflections that compose $Q$,
- Symbolic structure of the QR decomposition,

## Functions§

- Computes the numerical QR factorization of $A$.
- Computes the size and alignment of the workspace required to compute the numerical QR factorization of the matrix whose structure was used to produce the symbolic structure.
- Computes the symbolic QR factorization of a matrix $A$, given a fill-reducing column permutation, and the outputs of the pre-factorization steps.
- Computes the size and alignment of the workspace required to compute the symbolic QR factorization of a matrix with dimensions
`(nrows, ncols)`

.