Lossy data compression reduces communication time in hybrid time-parallel integrators

accepted for publication on 2017-09-22
  • Parallel in time methods for solving initial value problems are a means to increase the parallelism of numerical simulations. Hybrid parareal schemes interleaving the parallel in time iteration with an iterative solution of the individual time steps are among the most efficient methods for general nonlinear problems. Despite the hiding of communication time behind computation, communication has in certain situations a significant impact on the total runtime. Here we present strict, yet no sharp, error bounds for hybrid parareal methods with inexact communication due to lossy data compression, and derive theoretical estimates of the impact of compression on parallel efficiency of the algorithms. These and some computational experiments suggest that compression is a viable method to make hybrid parareal schemes robust with respect to low bandwidth setups.
Author:Lisa Fischer, Sebastian Götschel, Martin Weiser
Document Type:Article
Parent Title (English):Comput. Vis. Sci.
Year of first publication:2017