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These are input scripts used to run versions of several of the
benchmarks in the top-level bench directory using the GPU and
USER-CUDA accelerator packages. The results of running these scripts
on two different machines (a desktop with 2 Tesla GPUs and the ORNL
Titan supercomputer) are shown on the "GPU (Fermi)" 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 GPU and USER-CUDA sub-sections of the
doc/Section_accelerate.html file also describes this process.
Make.py -d ~/lammps -j 16 -p #all orig -m linux -o cpu exe
Make.py -d ~/lammps -j 16 -p #all opt orig -m linux -o opt exe
Make.py -d ~/lammps -j 16 -p #all omp orig -m linux -o omp exe
Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \
-gpu mode=double arch=20 -o gpu_double libs exe
Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \
-gpu mode=mixed arch=20 -o gpu_mixed libs exe
Make.py -d ~/lammps -j 16 -p #all gpu orig -m linux \
-gpu mode=single arch=20 -o gpu_single libs exe
Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \
-cuda mode=double arch=20 -o cuda_double libs exe
Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \
-cuda mode=mixed arch=20 -o cuda_mixed libs exe
Make.py -d ~/lammps -j 16 -p #all cuda orig -m linux \
-cuda mode=single arch=20 -o cuda_single libs exe
Make.py -d ~/lammps -j 16 -p #all intel orig -m linux -o intel_cpu exe
Make.py -d ~/lammps -j 16 -p #all kokkos orig -m linux -o kokkos_omp exe
Make.py -d ~/lammps -j 16 -p #all kokkos orig -kokkos cuda arch=20 \
-m cuda -o kokkos_cuda exe
Make.py -d ~/lammps -j 16 -p #all opt omp gpu cuda intel kokkos orig \
-gpu mode=double arch=20 -cuda mode=double arch=20 -m linux \
-o all libs exe
Make.py -d ~/lammps -j 16 -p #all opt omp gpu cuda intel kokkos orig \
-kokkos cuda arch=20 -gpu mode=double arch=20 \
-cuda mode=double arch=20 -m cuda -o all_cuda libs exe
------------------------------------------------------------------------
To run on just CPUs (without using the GPU or USER-CUDA styles),
do something like the following:
mpirun -np 1 lmp_linux_double -v x 8 -v y 8 -v z 8 -v t 100 < in.lj
mpirun -np 12 lmp_linux_double -v x 16 -v y 16 -v z 16 -v t 100 < in.eam
The "xyz" settings determine the problem size. The "t" setting
determines the number of timesteps.
These mpirun commands run on a single node. To run on multiple
nodes, scale up the "-np" setting.
------------------------------------------------------------------------
To run with the GPU package, do something like the following:
mpirun -np 12 lmp_linux_single -sf gpu -v x 32 -v y 32 -v z 64 -v t 100 < in.lj
mpirun -np 8 lmp_linux_mixed -sf gpu -pk gpu 2 -v x 32 -v y 32 -v z 64 -v t 100 < in.eam
The "xyz" settings determine the problem size. The "t" setting
determines the number of timesteps. The "np" setting determines how
many MPI tasks (per node) the problem will run on. The numeric
argument to the "-pk" setting is the number of GPUs (per node); 1 GPU
is the default. Note that you can use more MPI tasks than GPUs (per
node) with the GPU package.
These mpirun commands run on a single node. To run on multiple nodes,
scale up the "-np" setting, and control the number of MPI tasks per
node via a "-ppn" setting.
------------------------------------------------------------------------
To run with the USER-CUDA package, do something like the following:
mpirun -np 1 lmp_linux_single -c on -sf cuda -v x 16 -v y 16 -v z 16 -v t 100 < in.lj
mpirun -np 2 lmp_linux_double -c on -sf cuda -pk cuda 2 -v x 32 -v y 64 -v z 64 -v t 100 < in.eam
The "xyz" settings determine the problem size. The "t" setting
determines the number of timesteps. The "np" setting determines how
many MPI tasks (per node) the problem will run on. The numeric
argument to the "-pk" setting is the number of GPUs (per node); 1 GPU
is the default. Note that the number of MPI tasks must equal the
number of GPUs (both per node) with the USER-CUDA package.
These mpirun commands run on a single node. To run on multiple nodes,
scale up the "-np" setting, and control the number of MPI tasks per
node via a "-ppn" setting.
------------------------------------------------------------------------
If the script has "titan" in its name, it was run on the Titan
supercomputer at ORNL.
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