1 research outputs found
Using performance analysis tools for parallel-in-time integrators -- Does my time-parallel code do what I think it does?
While many ideas and proofs of concept for parallel-in-time integration
methods exists, the number of large-scale, accessible time-parallel codes is
rather small. This is often due to the apparent or subtle complexity of the
algorithms and the many pitfalls awaiting developers of parallel numerical
software. One example of such a time-parallel code is pySDC, which implements,
among others, the parallel full approximation scheme in space and time
(PFASST). Inspired by nonlinear multigrid ideas, PFASST allows to integrate
multiple time-steps simultaneously using a space-time hierarchy of spectral
deferred corrections. In this paper we demonstrate the application of
performance analysis tools to the PFASST implementation pySDC. Tracing the path
we took for this work, we highlight the obstacles encountered, describe
remedies and explain the sometimes surprising findings made possible by the
tools. Although focusing only on a single implementation of a particular
parallel-in-time integrator, we hope that our results and in particular the way
we obtained them are a blueprint for other time-parallel codes.Comment: 31 pages, 15 figures, CVS Proceedings of the 9th PinT Worksho