HOOMD-blue

HOOMD-blue is a general purpose particle simulation toolkit. It performs molecular dynamics simulations of particles with a variety of pair, bond, angle, and other potentials. HOOMD-blue runs fast on NVIDIA GPUs, and can scale across many nodes. For more information, see the HOOMD-blue website.

Installing HOOMD-blue

Official binaries of HOOMD-blue are available via conda through the glotzer channel. To install HOOMD-blue, first download and install miniconda following conda's instructions. Then add the glotzer channel and install HOOMD-blue:

$ conda config --add channels glotzer
$ conda install hoomd

Compiling HOOMD-blue

Use cmake to configure an out of source build and make to build hoomd.

mkdir build
cd build
cmake ../
make -j20

For more detailed instructions, see the documentationn.

Prerequisites

• Required:
  • Python >= 2.6
  • boost >= 1.39.0
  • CMake >= 2.6.2
  • C++ Compiler (tested with gcc, clang, intel)
• Optional:
  • NVIDIA CUDA Toolkit >= 5.0
  • MPI (tested with OpenMPI, MVAPICH, impi)

Job scripts

HOOMD-blue job scripts are python scripts. You can control system initialization, run protocol, analyze simulation data, or develop complex workflows all with python code in your job.

Here is a simple example.

from hoomd_script import *
context.initialize()

# create 100 random particles of name A
init.create_random(N=100, phi_p=0.01, name='A')
# specify Lennard-Jones interactions between particle pairs
lj = pair.lj(r_cut=3.0)
lj.pair_coeff.set('A', 'A', epsilon=1.0, sigma=1.0)
# integrate at constant temperature
all = group.all();
integrate.mode_standard(dt=0.005)
integrate.nvt(group=all, T=1.2, tau=0.5)
# run 10,000 time steps
run(10e3)

Save this as lj.py and run with hoomd lj.py.

Documentation

Documentation for the current stable release is available online: http://codeblue.umich.edu/hoomd-blue/doc/

Change log

See ChangeLog.md.

Contributing to HOOMD-blue.

Contributions are welcomed via pull requests on Bitbucket.

0. First contact the HOOMD-blue developers prior to beginning your work to ensure that your plans mesh well with the planned development direction and standards set for the project. Then implement your code.
1. Submit a pull request on bitbucket. Multiple developers and/or users will review requested changes and make comments.
   • Bug fixes should be based on maint
   • New features should be based on master
2. The lead developer will merge your work into next to trigger continuous integration tests. These will compile and build your code in all supported configurations. Jenkins will e-mail you if your commits cause tests to fail. The Jenkins server is: https://petry.engin.umich.edu/.
3. The lead developer will merge into the mainline after the review is complete and approved.

• All contributors must agree to the Contributor Agreement (ContributorAgreement.md) before their pull request can be merged.
• All contributions must follow the source code style conventions (SourceConventions.md).
• The branch review checklist (BranchReviewChecklist.md)is a guide for reviewers to follow when reviewing a pull request.