Scientific Computation and Applied & Industrial Mathematics: Chen Greif

  • Date: 02/07/2017
  • Time: 12:30
Chen Greif, Department of Computer Science, The University of British Columbia

University of British Columbia


SPMR: a Family of Saddle-Point Minimum Residual Solvers


We introduce SPMR, a new family of methods for iteratively solving saddle-point systems
using a minimum or quasi-minimum residual approach. No symmetry assumptions are made.
The basic mechanism underlying the method is a novel simultaneous bidiagonalization procedure
that yields a simplified saddle-point matrix on a projected Krylov-like subspace, and allows for a
monotonic short-recurrence iterative scheme. We develop a few variants, demonstrate the advantages
of our approach, derive optimality conditions, and discuss connections to existing methods.
Numerical experiments illustrate the merits of this new family of methods.

This is joint work with Ron Estrin.

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Location: ESB 4133 (PIMS Lounge)