GPU Optimized Monte Carlo (GOMC)
GOMC is open-source software for simulating molecular systems using the Metropolis Monte Carlo algorithm. The software has been written in object oriented C++, and uses OpenMP and NVIDIA CUDA to allow for execution on multi-core CPU and GPU architectures. GOMC employs widely-used simulation file types (PDB, PSF, CHARMM-style parameter files) .
GOMC can be used to study vapor–liquid equilibria, adsorption in porous materials, surfactant self-assembly, and condensed phase structure for complex molecules. To learn more about GOMC, please refer to our documentation and recent published GOMC paper.
GOMC supports simulations in a variety of ensembles, which include:
- Grand canonical
- Gibbs ensemble (constant volume and pressure)
GOMC supports a variety of all-atom, united atom, and coarse grained force fields such as:
GOMC supports a variety of molecular topologies:
Monte Carlo moves
GOMC supports a variety of Monte Carlo moves, such as:
- Rigid-body displacement
- Rigid-body rotation
- Molecular regrowth using coupled-decoupled configurational-bias
- Crankshaft using a combination of crankshaft and coupled-decoupled configurational-bias
- Intra-box swap using coupled-decoupled configurational-bias
- Intra-box Molecular Exchange Monte Carlo
- Inter-box swap using coupled-decoupled configurational-bias
- Inter-box Molecular Exchange Monte Carlo
- Volume exchange (isotropic and anisotropic)
Multiparticle MC move
In the next release, GOMC will support Multiparticle MC move, where all molecules will displace and/or rotate simultaneously along the force. If you are interested to use this feature, click on this image to navigate to our GitHub repository.
In the next release, GOMC will support the parallel tempering in NVT, NPT, GCMC, and GEMC simulation. In GOMC, each replica can be run in parallel, using OpenMP. If you are interested to use this feature, click on this image to navigate to our GitHub repository.
In the Next release, GOMC will support free energy calculation in NVT and NPT ensemble, using TI, BAR, and MBAR methods. Post analysis of GOMC energy output can be done using alchemlyb python library, developed at Arizona State University. If you are interested to use this feature, click on this image to navigate to our GitHub repository.