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.

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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.

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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 CPUs the problem will be run on, and the "g" settings determines how many GPUs the problem will run on, i.e. 1 or 2 in this case. You can use more CPUs than GPUs with the GPU package.

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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 1 ../lmp_linux_double -sf cuda -v g 1 -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 CPUs the problem will be run on, and the "g" setting determines how many GPUs the problem will run on, i.e. 1 or 2 in this case. You can use more CPUs than GPUs with the GPU package. You should make the number of CPUs and number of GPUs equal for the USER-CUDA package.