DL_MONTE is a general purpose parallel Monte Carlo simulation package. The software has seen two major development phases up to now.
DL_MONTE-1 code was originally developed at Daresbury Laboratory by Dr John Purton under the auspices of EPSRC for the Collaborative Computational Project for the Computer Simulation of Condensed Phases (CCP5), and focused primarily on applications in materials science.
Since 2015 a research grant (EP/M011291/1) obtained from the EPSRC’s Software for the Future programme by Profs. Nigel Wilding (Physics, University of Bath), Steve Parker (Chemistry, University of Bath) and John Purton (Daresbury Laboratory) has funded the further, second developement phase - the DL_MONTE-2 project (as CCP5 Flagship).
The goal of the DL_MONTE-2 project is to convert DL_MONTE into a truly general purpose Monte Carlo (MC) engine, and to provide an MC simulation software that is inexpensive, accessible and sufficiently generalised to be used in broad academic research. That is, registered users have direct access to the source code for inspection and modification. In the spirit of the enterprise, contributions in the form of working code are welcome, provided the code is compatible with DL_MONTE-2 in regard to its interfaces and programming style and it is adequately documented.
One of the objectives of DL_MONTE-2 is also to provide an alternative (Monte Carlo) methodology for users of DL POLY. Therefore, experience of using DL_POLY would be advantageous for the user, as the DL_MONTE-2 I/O interface and overall workflow is very similar, albeit not identical, to that of DL_POLY. For example, the input to both programs is arranged via three compulsory input files: CONFIG, CONTROL and FIELD. DL_MONTE-2 also uses the same internal units as DL_POLY.
DL_MONTE can be obtained free of charge from our GitLab repository. The tutorials, tests and exercises can be downloaded directly without registration. However to download the source code you will be required to fill in a registration form. The information gained will be used as justification for the development of DL_MONTE and to obtain further funding. The form requires you to input your name, institution and email address. Once the submit button is clicked an email will be sent to you and will contain the password to decrypt the zip files. You will also be added to the DL_MONTE emailing list which will be used to notify users of new releases and training events (details will be forwarded to you on how to unsubscribe).
Some useful information on using DL_MONTE can be obtained from the following web pages:
TUTORIALS (Downloadable tutorial exercises and scripts from this link )
WIKI (Currently under construction)
NOTE: DL_MONTE-2 is released under a 4 clause BSD licence.
The main features and advanced MC methodologies available in DL_MONTE-2 are outlined below. The list is non-exhaustive as the MC engine functionality is constantly being extended. For details please refer to the DL_MONTE-2 manual.
Statistical EnsemblesBulk (XYZ PBC):
Canonical - NVT
Isobaric-isothermal - NPT
Grand Canonical - µVT
Planar nanopore (XY PBC):
NVT, µVT and NpT (isotension ensemble)
Force FieldsThe availability of force fields in DL_MONTE-2 is determined by the supported interatomic and intramolecular interaction potentials. Like in DL_POLY, the molecular topology and force field parameters are specified in a separate input file (FIELD). The main types of implemented interations are listed below (see also the manual).
Electrostatics - direct, Ewald summation, long-range MFA correction in planar slit geometry
Two-body - a set of bonded and non-bonded potentials
Three-body - a set of bonded and non-bonded potentials
Four-body - bonded: proper and improper dihedrals/torsions
Metals - Sutton/Chen, Gupta and EAM
User-defined - analytic and tabulated
The above set of interactions allows to set up a system with the following force-fields: CHARMM, AMBER, OPLS, Gromos as well as simplified (coarse-grained) models. Support of DL_MONTE-2 by the FIELD creation helper utility DL_FIELD is the work in progress currently.
Free energy difference (FED) methods
Umbrella sampling – harmonic or tabulated bias
Expanded/extended ensemble – iterative bias optimisation
Wang-Landau scheme – on-the-fly bias optimisation
Lattice/Phase-switch Monte Carlo – FED between two phases
Scenarios beyond conventional MC simulation
FED along volume in NpT ensemble
FED along the centre-of-mass separation for two atomic groups
FED in a range of temperatures or inverse temperatures (β)
Parallel replica-exchange in a range of temperatures (no FED)