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These are input scripts used to run GPU versions of several of the
benchmarks in the top-level bench directory. The results of running
these scripts on different machines are shown on the GPU section of
the Benchmark page of the LAMMPS WWW site (lammps.sandia.gov/bench).
Examples are shown below of how to run these scripts. This assumes
you have built 3 executables with both the GPU and USER-CUDA packages
installed, e.g.
lmp_linux_single
lmp_linux_mixed
lmp_linux_double
The precision (single, mixed, double) refers to the GPU and USER-CUDA
pacakge precision. See the README files in the lib/gpu and lib/cuda
directories for instructions on how to build the packages with
different precisions. The doc/Section_accelerate.html file also has a
summary description.
------------------------------------------------------------------------
If the script has "cpu" in its name, it is meant to be run in CPU-only
mode. For example:
mpirun -np 1 ../lmp_linux_double -c off -v x 8 -v y 8 -v z 8 -v t 100 < in.lj.cpu
mpirun -np 12 ../lmp_linux_double -c off -v x 16 -v y 16 -v z 16 -v t 100 < in.lj.cpu
The "xyz" settings determine the problem size. The "t" setting
determines the number of timesteps.
------------------------------------------------------------------------
If the script has "gpu" in its name, it is meant to be run using
the GPU package. For example:
mpirun -np 12 ../lmp_linux_single -sf gpu -c off -v g 1 -v x 32 -v y 32 -v z 64 -v t 100 < in.lj.gpu
mpirun -np 8 ../lmp_linux_mixed -sf gpu -c off -v g 2 -v x 32 -v y 32 -v z 64 -v t 100 < in.lj.gpu
The "xyz" settings determine the problem size. The "t" setting
determines the number of timesteps. The "np" setting determines how
many MPI tasks per compute node the problem will run on, and the "g"
setting determines how many GPUs per compute node the problem will run
on, i.e. 1 or 2 in this case. Note that you can use more MPI tasks
than GPUs (both per compute node) with the GPU package.
------------------------------------------------------------------------
If the script has "cuda" in its name, it is meant to be run using
the USER-CUDA package. For example:
mpirun -np 1 ../lmp_linux_single -sf cuda -v g 1 -v x 16 -v y 16 -v z 16 -v t 100 < in.lj.cuda
mpirun -np 2 ../lmp_linux_double -sf cuda -v g 2 -v x 32 -v y 64 -v z 64 -v t 100 < in.eam.cuda
The "xyz" settings determine the problem size. The "t" setting
determines the number of timesteps. The "np" setting determines how
many MPI tasks per compute node the problem will run on, and the "g"
setting determines how many GPUs per compute node the problem will run
on, i.e. 1 or 2 in this case. For the USER-CUDA package, the number
of MPI tasks and GPUs (both per compute node) must be equal.
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