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| DL_POLY | |
|---|---|
| Name | DL_POLY |
| Developer | Daresbury Laboratory |
| Released | 1990s |
| Latest release | See Versions and Development |
| Programming language | Fortran |
| Operating system | Unix-like |
| Genre | Molecular dynamics |
| License | Varies (proprietary and open-source variants) |
DL_POLY
DL_POLY is a general-purpose molecular dynamics simulation package developed originally at the Daresbury Laboratory for atomistic modelling of condensed matter. It has been used across computational chemistry, materials science, and biophysics communities to study liquids, solids, interfaces, and defects with a focus on speed and scalability. The code has influenced high-performance computing practices at institutions such as CERN, Oak Ridge National Laboratory, Argonne National Laboratory, and Los Alamos National Laboratory.
DL_POLY traces its origins to computational efforts at Daresbury Laboratory in the 1990s, where researchers adapted classical molecular dynamics methods pioneered at places like Los Alamos National Laboratory and Sandia National Laboratories. Early versions were influenced by algorithms developed at IBM research centers and by force fields formalized at Cornell University and Columbia University. Over successive releases the project incorporated parallelization techniques emerging from projects at Lawrence Livermore National Laboratory and software engineering practices used at National Institute for Computational Sciences. Collaborations and user-driven features connected DL_POLY to workflows at Imperial College London, University of Cambridge, Stanford University, Massachusetts Institute of Technology, and University of California, Berkeley.
DL_POLY implements classical potentials and integration schemes to model atomic-scale dynamics for systems ranging from molecular liquids studied at Royal Society-affiliated groups to crystalline materials explored at Max Planck Society institutes. The package supports multiple force fields used in communities at University of Oxford, ETH Zurich, and Princeton University. Capabilities include long-range electrostatics methods employed by researchers at Harvard University, thermostats and barostats comparable to those used at California Institute of Technology labs, and free energy sampling methods similar to approaches adopted at University of Chicago. The software can simulate systems relevant to experiments at facilities such as Diamond Light Source, European Synchrotron Radiation Facility, and Brookhaven National Laboratory.
DL_POLY uses integrators and potential evaluation routines rooted in algorithms developed at Los Alamos National Laboratory and refined in literature from Cornell University and Johns Hopkins University. For electrostatics it implements Ewald summation variants and particle-mesh techniques akin to those used at Princeton University and Columbia University; neighbor-list and cell-linked approaches reflect methods from Lawrence Livermore National Laboratory. Constraint handling and rigid-body dynamics in DL_POLY parallel implementations draw on advances from Argonne National Laboratory and Oak Ridge National Laboratory. Implementation choices often mirror numerical techniques reported by research groups at KTH Royal Institute of Technology and University of Toronto.
Development of DL_POLY proceeded through major numbered releases, with contributions from staff at Daresbury Laboratory and collaborators at University of Manchester, University of Bristol, University of Edinburgh, and University of Leeds. Later branches and forks incorporated modern parallel paradigms championed by teams at NVIDIA, Intel Corporation, AMD, and high-performance computing centers including UK National Supercomputer Service and PRACE. Version history reflects cross-institutional input similar to multi-institution projects at European Molecular Biology Laboratory and Wellcome Trust-funded consortia. Maintenance and documentation efforts paralleled editorial practices at Oxford University Press and Cambridge University Press publications.
DL_POLY was designed with parallel performance in mind, adopting domain decomposition strategies comparable to those used by codes from Argonne National Laboratory and Oak Ridge National Laboratory. Benchmarks have been performed on systems maintained by National Energy Research Scientific Computing Center, NERSC, and regional centers such as ARCHER and HPC Wales. Parallel scaling exploits message-passing paradigms consistent with Message Passing Interface deployments at European Centre for Medium-Range Weather Forecasts and multi-threading approaches similar to work at Lawrence Berkeley National Laboratory. Optimizations for vector processors and accelerators were informed by collaborations with Cray Research, NVIDIA GPU initiatives, and compiler strategies from Intel Corporation.
Researchers at University of Cambridge, Imperial College London, ETH Zurich, and Max Planck Society have used DL_POLY for studying phase transitions, defect dynamics, and transport properties. The package has supported simulations connected to experimental campaigns at ISIS Neutron and Muon Source, Oak Ridge National Laboratory Spallation Neutron Source, and Argonne National Laboratory beamlines. Applications include investigations of ionic liquids relevant to work at University of Manchester and University College London, polymer dynamics studied by groups at University of Massachusetts Amherst and Northwestern University, and nanoparticle interfaces explored at California Institute of Technology and University of Illinois Urbana-Champaign.
DL_POLY reads and writes input and output files compatible with common workflows developed at Rutherford Appleton Laboratory and data practices used by research communities at European Molecular Biology Laboratory and Wellcome Sanger Institute. Typical files include configuration, field, and control records analogous to formats adopted by packages from Sandia National Laboratories and exchange formats influenced by initiatives at CODATA and Research Data Alliance. Output supports trajectory analysis consistent with tools used at Max Planck Institute for Polymer Research and visualization platforms employed at Lawrence Livermore National Laboratory.
Category:Computational chemistry software