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update Kokkos related documentation about JIT compilation and UVM.

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Axel Kohlmeyer
2020-05-11 18:07:51 -04:00
parent 23c55b0046
commit a6cfe8f642
1 changed files with 15 additions and 9 deletions
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doc/src/Build_extras.rst
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@ -320,12 +320,13 @@ to have an executable that will run on this and newer architectures.
.. 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
@ -580,9 +581,14 @@ recommended when developing a Kokkos-enabled style in LAMMPS.
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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