Lammps

Lammps minimal install on Linux

1. Download Lammps current C++ tarball and extract it.

2. Install either OpenMPI or MPICH2. I found that MPICH2 works slightly better. You will need both the base and development packages for your system. For example:

yum install mpich2.x86_64

yum install mpich2-devel.x86_64

Note where the framework has been installed.

3. Set your PATH to point to the MPI binaries. Edit the user's .bash_profile and add the MPI bin directory to the existing PATH modification there. This will take effect on your next session. To add to PATH on your current session, type (use the correct bin directory location)

export PATH=$PATH:/lib64/mpich2/bin

4. Make sure the system can find the MPI libraries. Open /etc/ld.so.conf. It should either contain a list of library directories or something like

include ld.so.conf.d/*.conf

In the first case, add you MPI library directory, for example:

/lib64/mpich2/lib

In the latter case, go to the folder mentioned in the include and create a new file. Make sure it conforms to the format specified in the include statement. Put your MPI library directory path into that file.

5. Download the minmpi makefile and put into your lammps directory in src/MAKE.

6. Go to the src directory and type (the -j switch uses parallel compilation; remove it if causes problems)

make -j minmpi

7. If no errors occur, you now have the executable file lmp_minmpi. If the compilation failed because of missing dependencies, you need to specify the location of MPI includes and libraries for lammps. Edit Makefile.minmpi, and make sure that MPI_INC points to the location of mpi.h, MPI_PATH points to the libraries and MPI_LIB links the MPI. For example:

MPI_INC = -I/usr/include/mpich2-x86_64/

MPI_PATH = -L/lib64/mpich2/lib

MPI_LIB = lmpi

Go back to src and type

make clean-all

make -j minmpi

Scaling tests

Lammps calculation time scales linearly with the number of atoms and increasing the number of processors decreases calculation time proportionally. It distributes well among different processor nodes. Simulations were run with a timestep of 1 ps for 10 000 timesteps.

• 

  Size scaling

• 

  Processor scaling

• 

  Nodes scaling

Random seed tests

Tests for the random seed in LAMMPS command "velocity" (http://lammps.sandia.gov/doc/velocity.html) were performed.

results:

when using same number of different processors with the same random seed, the velocities created in simulatsions with identical inputs were the same.

when using different number of processors with the same random seed, the velocities created in simulations with identical inputs were different.

Naturally, when using different random seed in simulations with identical input, the velocities created were different.

The results were also tested to hold for both uniform and gaussian velocity distributions.