Package: hymd
HylleraasMD(HyMD) is a massively parallel Python package for Hamiltonian hybrid particle-field molecular dynamics (HhPF-MD) simulations of coarse-grained bio- and soft-matter systems.HyMD can run canonical hPF-MD simulations, or filtered density Hamiltonian hPF (HhPF-MD) simulations[1],[2],[3]with or without explicit PME electrostatic interactions. It includes all standard intramolecular interactions,
including stretching, bending, torsional, and combined bending-dihedral potentials. Additionally, topological reconstruction of permanent peptide chain backbone dipoles is possible for accurate recreation of protein conformational dynamics.
It can run simulations in constant energy (NVE), constant volume (NVT)[1]or constant pressure (NPT) conditions[4].HyMD uses thepmeshlibrary for particle-mesh operations, with the PPFT[5]backend for FFTs through thepfft-python bindings.
File IO is done via HDF5 formats to allow MPI parallel reads.If you use HyMD,please cite our paper(s).User GuideDetailed installation and user guide, together with comprehensive example simulations are located in theHylleraasMD documentation.Run simulations bypython3-mhymd[CONFIGURATION_FILE][TOPOLOGY_FILE](--OPTIONAL_ARGS)Run interactively in Google ColaboratoryAGoogle Colaboratoryjupyter notebook is setupherewith a working HyMD fully installed and executable in the browser.InstallationNon-Python dependenciesHyMD installationrequiresa working MPI compiler. It is highly recommended to haveMPI-enabledHDF5 andh5pyfor running parallel simulations with HyMD. Install both on Ubuntu withsudoapt-getupdate-y
sudoapt-getinstall-ypkg-configlibhdf5-mpi-devlibopenmpi-dev
python3-mpipuninstallh5py# Remove any serial h5py installation presentCC="mpicc"HDF5_MPI="ON"python3-mpipinstall--no-binary=h5pyh5pyNoteThere might be memory leaks if you use OpenMPI <= 4.1.1. See#186for more details.Python dependenciesInstall HyMD withpipbypython3-mpipinstall--upgradenumpympi4pycython
python3-mpipinstall"pmesh @ git+https://github.com/rainwoodman/pmesh"python3-mpipinstallhymdpmeshis installed from the GitHub repository because fixes to be compatible with modern NumPy versions were not pushed to PyPI.
SeeHyMD docsfor more information, including install steps for macOS and non-Debian linux distributions.Run in dockerAlternatively, an up-to-date docker image is available fromdocker hubdockerpullmortele/hymd
dockerrun-itmortele/hymd
/app$python3-mpipinstallhymd
/app$
/app$# Grab example input files/app$curl-Ohttps://raw.githubusercontent.com/Cascella-Group-UiO/HyMD-tutorial/main/ideal_chain/ideal_chain.toml
/app$curl-Ohttps://raw.githubusercontent.com/Cascella-Group-UiO/HyMD-tutorial/main/ideal_chain/ideal_chain.HDF5
/app$
/app$# Run simulation/app$python3-mhymdideal_chain.tomlideal_chain.HDF5--verboseRun testsClone the repository and run tests withpytestgitclonehttps://github.com/Cascella-Group-UiO/HyMD.githymdcdhymd
python3-mpipinstallpytestpytest-mpi
pytestRunning MPI enabled pytest tests is simplified with a convenient scriptchmod+xpytest-mpi
pytest-mpi-oo-n2-nsContributions and issuesWe welcome contributions to our code and provide a set of guidelines to follow inCONTRIBUTING.md.To seek support in case of any issues and bugs, we welcome you to post them using theissue tracker.Please cite our workYou will find information about our publications and archived data since 2023 at the open repository:Publications.If you use HyMD, please cite:@article{Ledum_HylleraasMD_Massively_parallel_2023,author={Ledum, Morten and Carrer, Manuel and Sen, Samiran and Li, Xinmeng and Cascella, Michele and Bore, Sigbjørn Løland},doi={10.21105/joss.04149},journal={Journal of Open Source Software},month={apr},number={84},pages={4149},title={{HylleraasMD: Massively parallel hybrid particle-field molecular dynamics in Python}},url={https://joss.theoj.org/papers/10.21105/joss.04149},volume={8},year={2023}}@article{Sen_HylleraasMD_2023,author={Sen, Samiran and Ledum, Morten and Bore, Sigbjørn Løland and Cascella, Michele},title={Soft Matter under Pressure: Pushing Particle–Field Molecular Dynamics to the Isobaric Ensemble},doi={10.1021/acs.jcim.3c00186},journal={Journal of Chemical Information and Modeling},month=mar,year={2023},volume={63},number={7},pages={2207-2217},URL={https://doi.org/10.1021/acs.jcim.3c00186},}References[1]Ledum, M.; Sen, S.; Li, X.; Carrer, M.; Feng Y.; Cascella, M.; Bore, S. L. HylleraasMD: A Domain Decomposition-Based Hybrid Particle-Field Software for Multi-Scale Simulations of Soft Matter. ChemRxiv 2021[2]Ledum, M.; Carrer, M.; Sen, S.; Li, X.; Cascella, M.; Bore, S. L. HyMD: Massively parallel hybrid particle-field molecular dynamics in Python. Journal of Open Source Software (JOSS) 2023, 8(84), 2475-9066, 4149.[3]Bore, S. L.; Cascella, M. Hamiltonian and alias-free hybrid particle–field molecular dynamics. J. Chem. Phys. 2020, 153, 094106.[4]Sen, S.; Ledum, M.; Bore, S. L.; Cascella, M. Soft Matter under Pressure: Pushing Particle–Field Molecular Dynamics to the Isobaric Ensemble. J Chem Inf Model 2023, 63(7), 1549-9596.[5]Pippig, M. PFFT: An extension of FFTW to massively parallel architectures. SIAM J. Sci. Comput. 2013, 35, C213–C236.