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cuthill-mckee

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cuthill-mckee

A bandwidth reducing preconditioner for sparse matrices


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cuthill-mckee

The reverse Cuthill-Mckee method is a fast and effective preconditioner for reducing the bandwidth of sparse linear systems. When solving a positive semidefinite linear system using Cholesky factorization, it greatly reduces fill-in. For example, here is the Laplacian matrix of the Stanford bunny:

BEFORE:

AFTER:

example

var coeffs = [
  [0, 0, 1],
  [0, 2, 3],
  [1, 1, 1],
  [2, 2, 1]
]

var perm = require('cuthill-mckee')(coeffs, 3)

console.log(perm)

install

npm i cuthill-mckee

usage

require('cuthill-mckee')(list, n)

This module takes the coefficients of a sparse matrix as input and gives permutation which reduces the fill-in (or bandwidth) of the matrix.

  • list is a list of matrix coefficeints
  • n is the number of rows & columns in the matrix

Returns A permutation encoded as an array which preconditions the matrix.

license

(c) 2015 Mikola Lysenko. MIT

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Package last updated on 24 Jul 2017

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