1 research outputs found
Prestructuring sparse matrices with dense rows and columns via null space methods
Several applied problems may produce large sparse matrices with a small
number of dense rows and/or columns, which can adversely affect the performance
of commonly used direct solvers. By posing the problem as a saddle point
system, an unconventional application of a null space method can be employed to
eliminate dense rows and columns. The choice of null space basis is critical in
retaining the overall sparse structure of the matrix. A one-sided application
of the null space method is also presented to eliminate either dense rows or
columns. These methods can be considered techniques that modify the nonzero
structure of the matrix before employing a direct solver, and may result in
improved direct solver performance