This book looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysis and theoretical computer scientists alike.

Inhalt
An introduction to chordal graphs and clique trees.- Cutting down on fill using nested dissection: Provably good elimination orderings.- Automatic Mesh Partitioning.- Structural representations of Schur complements in sparse matrices.- Irreducibility and primitivity of Perron complements: Application of the compressed directed graph.- Predicting structure in nonsymmetric sparse matrix factorizations.- Highly parallel sparse triangular solution.- The fan-both family of column-based distributed Cholesky factorization algorithms.- Scalability of sparse direct solvers.- Sparse matrix factorization on SIMD parallel computers.- The efficient parallel iterative solution of large sparse linear systems.