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895ca766eeecefficient_neuronet

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			The in.kokkos input script is a copy of the bench/in.lj script,
			but can be run with the KOKKOS package,

			To run it, you must first build LAMMPS with the KOKKOS package
			installed, following the steps explained in Section 2.3.4 of
			doc/Section_start.html. An overview of building and running LAMMPS
			with the KOKKOS package, for different compute-node hardware on your
			machine, is given in Section 5.8 of doc/Section_accelerate.html.

			The example log files included in this directory are for a desktop box
			with dual hex-core CPUs and 2 GPUs.

			Two executables were built in the following manner:

			make yes-kokkos
			make g++ OMP=yes -> lmp_cpu
			make cuda CUDA=yes -> lmp_cuda

			Then the following runs were made. The "->" means that the run
			produced log.lammps which was then copied to the named log file.

			* MPI-only runs

			lmp_cpu -k off < in.kokkos -> log.kokkos.date.mpionly.1
			mpirun -np 4 lmp_cpu -k off < in.kokkos -> log.kokkos.date.mpionly.4

			* OpenMP threaded runs on CPUs only

			lmp_cpu -k on t 1 -sf kk < in.kokkos.half -> log.kokkos.date.cpu.1
			lmp_cpu -k on t 4 -sf kk < in.kokkos -> log.kokkos.date.cpu.4

			Note that in.kokkos.half was use for one of the runs, which uses the
			package command to force the use of half neighbor lists which are
			faster when running on just 1 thread.

			* GPU runs on 1 or 2 GPUs

			lmp_cuda -k on t 6 -sf kk < in.kokkos -> log.kokkos.date.gpu.1
			mpirun -np 2 lmp_cuda -k on t 6 -sf kk < in.kokkos -> log.kokkos.date.gpu.2

			Note that this is a very small problem (32K atoms) to run
			on 1 or 2 GPUs.