Version 1.2.0

26th September 2016

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HSL_MI35 Sparse least squares: incomplete factorization preconditioner

HSL_MI35 computes an incomplete factorization preconditioner that may be used in the solution of weighted sparse linear least squares problems. Given an m × n (m n) sparse matrix A = {aij} and an m × m diagonal matrix of weights W, HSL_MI35 computes an incomplete factorization of the matrix

C = ATW2A.

The matrix C may be optionally reordered, scaled and, if necessary, shifted to avoid breakdown of the factorization. The computed lower triangular matrix L is such that LLT is an incomplete factorization of

C¯ = SQTCQS + αI,

where Q is a permutation matrix, S is a diagonal scaling matrix and α is a non-negative shift. The incomplete factorization may be used for preconditioning when solving the normal equations

ATW2Ax = ATW2b.

A separate entry performs the preconditioning operation

y = Pz

where P = (L¯L¯T)1 is the incomplete factorization preconditioner and L¯ = QS1L.

The incomplete factorization is based on a matrix decomposition of the form

C¯ = LLT + LRT + RLT E,

where L is lower triangular with positive diagonal entries, R is a strictly lower triangular matrix with small entries that is used to stabilize the factorization process, and E has the structure

E = RRT + F + FT,

where F is strictly lower triangle. F is discarded while R is used in the computation of L but is then discarded. The user controls the dropping of small entries from L and R and the maximum number of entries within each column of L and R (and thus the amount of memory for L and the intermediate work and memory used in computing the incomplete factorization).

The incomplete factorization may be computed with or without forming C explicitly; the advantage of the latter option being that less memory is required.