Factoring matrices with a tree-structured sparsity pattern

Let A be a matrix whose sparsity pattern is a tree with maximal degree d_max. We show that if the columns of A are ordered using minimum degree on |A|+|A|^∗, then factoring A using a sparse LU with partial pivoting algorithm generates only O(d_maxn) fill, requires only O(d_maxn) operations, and is much more stable than LU with partial pivoting on a general matrix. We also propose an even more efficient and just-as-stable algorithm called sibling-dominant pivoting. This algorithm is a strict partial pivoting algorithm that modifies the column preordering locally to minimize fill and work. It leads to only O(n) work and fill. More conventional column pre-ordering methods that are based (usually implicitly) on the sparsity pattern of |A|^∗|A| are not as efficient as the approaches that we propose in this paper.