Krylov subspace methods with fixed memory requirements: Nearly Hermitian linear systems and subspace recycling

Soodhalter, Kirk M.

by Kirk M. Soodhalter

Abstract:

Krylov subspace iterative methods provide an effective tool for reducing the solution of large linear systems to a size for which a direct solver may be applied. However, the problems of limited storage and speed are still a concern. Therefore, in this dissertation work, we present iterative Krylov subspace algorithms for non-Hermitian systems which do have fixed memory requirements and have favorable convergence characteristics.

Reference:

Krylov subspace methods with fixed memory requirements: Nearly Hermitian linear systems and subspace recycling (Kirk M. Soodhalter), PhD thesis, Temple University, 2012.

Bibtex Entry:

@PHDTHESIS{S.2012,
  author = {Kirk M. Soodhalter},
  title = {Krylov subspace methods with fixed memory requirements: Nearly Hermitian
	linear systems and subspace recycling},
  school = {Temple University},
  year = {2012},
  abstract = {Krylov subspace iterative methods provide an effective tool for reducing
	the solution of large linear systems to a size for which a direct
	solver may be applied. However, the problems of limited storage and
	speed are still a concern. Therefore, in this dissertation work,
	we present iterative Krylov subspace algorithms for non-Hermitian
	systems which do have fixed memory requirements and have favorable
	convergence characteristics.},
  keywords = {thesis},
  owner = {kirk},
  timestamp = {2012.08.16}
}