update Kokkos related documentation about JIT compilation and UVM.

.. note::

   If you run Kokkos on a newer GPU architecture than what LAMMPS was

   compiled with, there will be a delay during device initialization

   since the just-in-time compiler has to recompile all GPU kernels

   for the new hardware.  This is, however, not possible when compiled

   for NVIDIA GPUs with CC 3.x (Kepler) for GPUs with CC 5.0 (Maxwell)

   and newer as they are not compatible.

   If you run Kokkos on a different GPU architecture than what LAMMPS

   was compiled with, there will be a delay during device initialization

   while the just-in-time compiler is recompiling all GPU kernels for

   the new hardware.  This is, however, only supported for GPUs of the

   **same** major hardware version and different minor hardware versions,

   e.g. 5.0 and 5.2 but not 5.2 and 6.0.  LAMMPS will abort with an

   error message indicating a mismatch, if that happens.

The settings discussed below have been tested with LAMMPS and are

confirmed to work.  Kokkos is an active project with ongoing improvements

The CMake option ``-DKokkos_ENABLE_CUDA_UVM=on`` or the makefile

setting ``KOKKOS_CUDA_OPTIONS=enable_lambda,force_uvm`` enables the

use of CUDA "Unified Virtual Memory" in Kokkos.  Please note, that

the LAMMPS KOKKOS package must **always** be compiled with the

*enable_lambda* option when using GPUs.

use of CUDA "Unified Virtual Memory" (UVM) in Kokkos.  UVM allows to

transparently use RAM on the host to supplement the memory used on the

GPU (with some performance penalty) and thus enables running larger

problems that would otherwise not fit into the RAM on the GPU.

Please note, that the LAMMPS KOKKOS package must **always** be compiled

with the *enable_lambda* option when using GPUs.  The CMake configuration

will thus always enable it.

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