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These are input scripts designed for use with the GPU package.
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These example scripts can be run with the USER-CUDA package, assuming
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you built LAMMPS with the package and the precision you want.
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To run them, you must first build LAMMPS with the GPU package
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installed, following the steps explained in Section 2.3 of
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doc/Section_start.html and lib/gpu/README. An overview of building
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and running LAMMPS with the GPU package is given in Section 5.6 of
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doc/Section_accelerate.html. Note that you can choose the precision
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at which computations are performed on the GPU in the build process.
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You can run any of the scripts as follows. You can also reset the
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x,y,z variables in the command line to change the size of the problem.
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Note that lines such as this in each of the input scripts:
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With the GPU package on 1 GPU:
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package gpu force/neigh 0 1 1
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lmp_machine -sf gpu < in.gpu.melt.2.5
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mpirun -np 8 lmp_machine -sf gpu < in.gpu.phosphate
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are set for running on a compute node with 2 GPUs. If you
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have a single GPU, you should comment out the line, since
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the default is 1 GPU per compute node.
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With the GPU package on 2 GPUs:
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The scripts can be run in the usual manner:
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mpirun -np 4 lmp_machine -sf gpu -pk gpu 2 tpa 8 < in.gpu.melt.5.0
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mpirun -np 12 lmp_machine -sf gpu -pk gpu 2 < in.gpu.rhodo
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lmp_g++ < in.gpu.melt.2.5
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lmp_g++ < in.gpu.melt.5.0
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lmp_g++ < in.gpu.phosphate
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lmp_g++ < in.gpu.rhodo
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CPU-only:
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mpirun -np 4 lmp_g++ < in.gpu.melt.2.5
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mpirun -np 4 lmp_g++ < in.gpu.melt.5.0
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mpirun -np 4 lmp_g++ < in.gpu.phosphate
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mpirun -np 4 lmp_g++ < in.gpu.rhodo
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lmp_machine < in.gpu.melt.2.5
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mpirun -np 4 lmp_machine < in.gpu.melt.5.0
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mpirun -np 8 lmp_machine < in.gpu.rhodo
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The first set of commmands will run a single MPI task using a single
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GPU (even if you have 2 GPUs).
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Note that with the GPU package you can have more MPI tasks
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than the number of GPUs (both per node).
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The second set of commands will run 4 MPI tasks, with 2 MPI tasks per
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GPU (if you have 2 GPUs), or 4 MPI tasks per GPU (if you have a single
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GPU).
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Also note that when running the in.gpu.melt.5.0 problem on the GPU,
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which has a long cutoff, the package gpu "tpa" setting should be > 1
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(e.g. 8) for best performance.
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@ -1,7 +1,5 @@
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# 3d Lennard-Jones melt
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package gpu 1
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variable x index 2
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variable y index 2
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variable z index 2
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@ -21,7 +19,7 @@ mass 1 1.0
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velocity all create 1.44 87287 loop geom
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pair_style lj/cut/gpu 2.5
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pair_style lj/cut 2.5
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pair_coeff 1 1 1.0 1.0 2.5
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neighbor 0.3 bin
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@ -1,7 +1,5 @@
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# 3d Lennard-Jones melt
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package gpu 1 tpa 8
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variable x index 2
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variable y index 2
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variable z index 2
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@ -21,7 +19,7 @@ mass 1 1.0
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velocity all create 1.44 87287 loop geom
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pair_style lj/cut/gpu 5.0
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pair_style lj/cut 5.0
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pair_coeff 1 1 1.0 1.0 5.0
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neighbor 0.3 bin
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@ -1,14 +1,13 @@
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# GI-System
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units metal
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package gpu 1
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atom_style charge
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read_data data.phosphate
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replicate 3 3 3
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pair_style lj/cut/coul/long/gpu 15.0
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pair_style lj/cut/coul/long 15.0
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pair_coeff 1 1 0.0 0.29
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pair_coeff 1 2 0.0 0.29
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pair_coeff 2 3 0.004251 1.91988674
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pair_coeff 3 3 0.012185 2.91706967
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kspace_style pppm/gpu 1e-5
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kspace_style pppm 1e-5
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neighbor 2.0 bin
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@ -27,4 +26,3 @@ timestep 0.001
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fix 1 all npt temp 400 400 0.01 iso 1000.0 1000.0 1.0
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run 200
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unfix 1
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@ -1,7 +1,5 @@
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# Rhodopsin model
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package gpu 1
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variable x index 2
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variable y index 2
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variable z index 2
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@ -14,9 +12,9 @@ bond_style harmonic
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angle_style charmm
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dihedral_style charmm
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improper_style harmonic
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pair_style lj/charmm/coul/long/gpu 8.0 10.0
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pair_style lj/charmm/coul/long 8.0 10.0
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pair_modify mix arithmetic
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kspace_style pppm/gpu 1e-4
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kspace_style pppm 1e-4
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read_data data.rhodo
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