Solver Selection Techniques for Sparse Linear Systems

Date and time: 
Monday, May 20, 2019 - 16:30
Location: 
200 Deschutes
Author(s):
Kanika Sood
University of Oregon
Host/Committee: 
  • Boyana Norris (Chair)
  • Dejing Dou
  • Lei Jiao
  • Elizabeth Bohls, English
  • Elizabeth Jessup, University of Colorado Boulder
Abstract: 

Scientific and engineering applications are dominated by linear algebra and depend on scalable solutions of sparse linear systems. For large problems, preconditioned iterative methods are a popular choice. High-performance numerical libraries offer a variety of preconditioned Newton-Krylov methods for solving sparse problems. However, the selection of a well-performing Krylov method remains to be the user's responsibility. This research presents the technique for choosing well-performing parallel sparse linear solver methods, based on the problem characteristics and the amount of communication involved in the Krylov methods.