# Module extendr_api::prelude::sparse::linalg::cholesky::supernodal

## Expand description

Supernodal factorization module.

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

## Structs§

- Cholesky Bunch-Kaufman factors containing both the symbolic and numeric representations.
- Cholesky LDLT factors containing both the symbolic and numeric representations.
- Cholesky LLT factor containing both its symbolic and numeric representations.
- A single supernode from the Cholesky factor.
- Cholesky factor structure containing its symbolic structure.
- Symbolic structure of a single supernode from the Cholesky factor.

## Functions§

- Computes the numeric values of the Cholesky Bunch-Kaufman factors of the matrix
`A`

with intranodal pivoting, and stores them in`L_values`

. - Returns the size and alignment of the workspace required to compute the numeric Cholesky Bunch-Kaufman factorization with intranodal pivoting of a matrix
`A`

with dimension`n`

. - Computes the numeric values of the Cholesky LDLT factors of the matrix
`A`

, and stores them in`L_values`

. - Returns the size and alignment of the workspace required to compute the numeric Cholesky LDLT factorization of a matrix
`A`

with dimension`n`

. - Computes the numeric values of the Cholesky LLT factor of the matrix
`A`

, and stores them in`L_values`

. - Returns the size and alignment of the workspace required to compute the numeric Cholesky LLT factorization of a matrix
`A`

with dimension`n`

. - Computes the supernodal symbolic structure of the Cholesky factor of the matrix
`A`

. - Returns the size and alignment of the workspace required to compute the symbolic supernodal factorization of a matrix of size
`n`

.