Profile and wavefront reduction of large sparse matrices based on spectral properties of a graph

This paper investigates profile and wavefront reduction of large sparse matrices of symmetric configuration. A new version of the Spectral Finite Element Graph Resequencing (SFR) algorithm is presented. This version, based on the Sturm Sequence Method , is compared with a previous implementation based on the subspace iteration Method (SIM), and is denoted here as . SFR type algorithms are effective to reorder vertices of generic graphs. These vertices can be associated to nodes or elements of finite element meshes. Several numerical examples are presented here. The numerical experiments include evaluation of algorithm performance using practical finite element meshes, a brief comparison between the and implementations, and assessment of the algorithm with respect to factorization of the associated system matrix. Moreover, the is also compared with previous resequencing algorithms, which are available in the technical literature.