Sparse matrices are first class objects in many VHLLs (very high level languages) used for scientific computing. They are a basic building block for various numerical and combinat...
The problem of writing high performance parallel applications becomes even more challenging when irregular, sparse or adaptive methods are employed. In this paper we introduce com...
Abstract. An efficient parallel algorithm is presented and tested for computing selected components of H−1 where H has the structure of a Hamiltonian matrix of two-dimensional la...
Lin Lin, Chao Yang, Jianfeng Lu, Lexing Ying, Wein...
A new software code for computing selected eigenvalues and associated eigenvectors of a real symmetric matrix is described. The eigenvalues are either the smallest or those closes...
For regular, sparse, linear systems, like those derived from regular grids, using High Performance Fortran (HPF) for iterative solvers is straightforward. However, for irregular ma...