  Modern accelerators use hierarchical parallel programming models that enable
massive multithreading within a processing element (PE), with multiple PEs per
device driven by traditional processes. Batching is a technique for exposing
PE-level parallelism in algorithms that have traditionally run on MPI processes
or multiple threads within a single process. Opportunities for batching arise
in, for example, kinetic discretizations of magnetized plasmas where collisions
are advanced in velocity space at each spatial point independently.
  This paper builds on previous work on a high-performance, fully nonlinear,
Landau collision operator by batching the linear solver, as well as batching
the spatial point problems and adding new support for multiple grids for
multiscale, multi-species problems. An anisotropic relaxation verification test
that agrees well with previous published results and analytical models is
presented. The performance results from NVIDIA A100 and AMD MI250X nodes are
presented with hardware utilization analysis for each architecture. The entire
implicit Landau operator time advance is implemented in Kokkos for performance
portability, running entirely on the device and is available in the PETSc
numerical library.
