Improving Multifrontal Methods by Means of Block Low-Rank Representations
Improving Multifrontal Methods by Means of Block Low-Rank Representations
Matrices coming from elliptic partial differential equations have been shown to have a low-rank property: well-defined off-diagonal blocks of their Schur complements can be approximated by low-rank products. Given a suitable ordering of the matrix which gives the blocks a geometrical meaning, such approximations can be computed using an SVD …