Wilkinson defined a sparse matrix as one with enough zeros that it pays to take advantage of
them. 1 This informal yet practical definition captures the essence of the goal of direct …

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics-a
very active area of research in which few up-to-date reference works are available. This is …

Supernode partitioning for unsymmetric matrices together with complete block diagonal
supernode pivoting and asynchronous computation can achieve high gigaflop rates for …

The subject of sparse matrices has its root in such diverse fields as management science,
power systems analysis, surveying, circuit theory, and structural analysis. Efficient use of …

JOREK is a massively parallel fully implicit non-linear extended magneto-hydrodynamic
(MHD) code for realistic tokamak X-point plasmas. It has become a widely used versatile …

Modeling of Resistivity and Acoustic Borehole Logging Measurements Using Finite Element
Methods provides a comprehensive review of different resistivity and sonic logging …

In fractured rocks, fluid flows mostly within a complex arrangement of fractures. Both the
fracture network structure and its hydraulic properties are determined at first order by the …

The PARDISO package is a mathematical library of OpenMP routines for the parallel direct
solution of large sparse linear systems of equations. One objective of PARDISO is to achieve …

We present a unified and self-contained treatment of rational Krylov methods for
approximating the product of a function of a linear operator with a vector. With the help of …

We investigate the use of low-rank approximations to reduce the cost of sparsedirect
multifrontal solvers. Among the different matrix representations that havebeen proposed to …