Large sparse linear systems of equations are ubiquitous in science engineering and beyond.
This open access monograph focuses on factorization algorithms for solving such systems. It
presents classical techniques for complete factorizations that are used in sparse direct
methods and discusses the computation of approximate direct and inverse factorizations that are
key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified
framework is used that emphasizes the underlying sparsity structures and highlights the
importance of understanding sparse direct methods when developing algebraic preconditioners.
Theoretical results are complemented by sparse matrix algorithm outlines. This monograph is
aimed at students of applied mathematics and scientific computing as well as computational
scientists and software developers who are interested in understanding the theory and
algorithms needed to tackle sparse systems. It is assumed that the reader has completed a basic
course in linear algebra and numerical mathematics.
