Cuthill–McKee algorithm

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Cuthill-McKee ordering of a matrix
RCM ordering of the same matrix

In the mathematical subfield of matrix theory, the Cuthill–McKee algorithm (CM), named for Elizabeth Cuthill and J. McKee ,[1] is an algorithm to permute a sparse matrix that has a symmetric sparsity pattern into a band matrix form with a small bandwidth. The reverse Cuthill–McKee algorithm (RCM) due to Alan George is the same algorithm but with the resulting index numbers reversed. In practice this generally results in less fill-in than the CM ordering when Gaussian elimination is applied.[2]

The Cuthill McKee algorithm is a variant of the standard breadth-first search algorithm used in graph algorithms. It starts with a peripheral node and then generates levels R_i for i=1, 2,.. until all nodes are exhausted. The set  R_{i+1} is created from set  R_i by listing all vertices adjacent to all nodes in  R_i . These nodes are listed in increasing degree. This last detail is the only difference with the breadth-first search algorithm.

Algorithm

Given a symmetric n\times n matrix we visualize the matrix as the adjacency matrix of a graph. The Cuthill–McKee algorithm is then a relabeling of the vertices of the graph to reduce the bandwidth of the adjacency matrix.

The algorithm produces an ordered n-tuple R of vertices which is the new order of the vertices.

First we choose a peripheral vertex (the vertex with the lowest degree) x and set R := ({x}).

Then for i = 1,2,\dots we iterate the following steps while |R| < n

  • Construct the adjacency set A_i of R_i (with R_i the i-th component of R) and exclude the vertices we already have in R
A_i := \operatorname{Adj}(R_i) \setminus R
  • Sort A_i with ascending vertex order (vertex degree).
  • Append A_i to the Result set R.

In other words, number the vertices according to a particular breadth-first traversal where neighboring vertices are visited in order from lowest to highest vertex order.

See also

References

  1. E. Cuthill and J. McKee. Reducing the bandwidth of sparse symmetric matrices In Proc. 24th Nat. Conf. ACM, pages 157–172, 1969.
  2. J. A. George and J. W-H. Liu, Computer Solution of Large Sparse Positive Definite Systems, Prentice-Hall, 1981