Large-scale multiphysics simulations are computationally challenging due to
the coupling of multiple processes with widely disparate time scales. The
advent of exascale computing systems exacerbates these challenges, since these
enable ever increasing size and complexity. Recently, there has been renewed
interest in developing multirate methods as a means to handle the large range
of time scales, as these methods may afford greater accuracy and efficiency
than more traditional approaches of using IMEX and low-order operator splitting
schemes. However, there have been few performance studies that compare
different classes of multirate integrators on complex application problems. We
study the performance of several newly developed multirate infinitesimal (MRI)
methods, implemented in the SUNDIALS solver package, on two reacting flow model
problems built on structured mesh frameworks. The first model revisits the work
of Emmet et al. (2014) on a compressible reacting flow problem with complex
chemistry that is implemented using BoxLib but where we now include comparisons
between a new explicit MRI scheme with the multirate spectral deferred
correction (SDC) methods in the original paper. The second problem uses the
same complex chemistry as the first problem, combined with a simplified flow
model, but run at a large spatial scale where explicit methods become
infeasible due to stability constraints. Two recently developed
implicit-explicit MRI multirate methods are tested. These methods rely on
advanced features of the AMReX framework on which the model is built, such as
multilevel grids and multilevel preconditioners. The results from these two
problems show that MRI multirate methods can offer significant performance
benefits on complex multiphysics application problems and that these methods
may be combined with advanced spatial discretization to compound the advantages
of both