===affil2:
Lawrence Livermore National Labratory
===firstname:
Ben
===firstname4:

===firstname3:
Thomas
===lastname2:
Schroder
===keyword1:
OTHER
===lastname:
O'Neill
===firstname5:

===affil6:

===lastname3:
Manteuffel
===email:
ben.oneill@colorado.edu
===keyword2:
Multigrid
===keyword_other2:

===lastname6:

===affil5:

===otherauths:

===lastname4:

===affil4:

===lastname7:

===competition:
no
===affil7:

===firstname7:

===postal:
2210 Walnut St Apt 1
Boulder CO 80302
===firstname6:

===ABSTRACT:
Standard sequential time marching schemes limit parallelism to the spacial domain. With computer architectures growing in size rather than clock speeds, additional speed-up must come from greater parallelism. We propose a multigrid reduction method that incorporates temporal parallelism into general time-stepping routines, allowing for dramatic speed-ups on large architectures. For a nonlinear equation, each iteration of the parallel-in-time method requires an expensive, nonlinear, spatial solve. Using a simple nonlinear equation, with a Picard method as the nonlinear solver, we investigate several methods for reducing the computational cost of this spatial solve, including reducing solver accuracy on coarser levels and introducing spatial coarsening.
===affil3:
University of Colorado Boulder
===keyword_other1:
Time Parallel Methods
===lastname5:

===affilother:

===title:
Parallel in time multigrid for Nonlinear Problems
===firstname2:
Jacob