Awesome

TaichiMD

Interactive, GPU-accelerated Molecular (& Macroscopic) Dynamics using the Taichi programming language

(05/26/2022) TaichiMD is now made compatible with taichi v1.0.

Goals

To extend capabilities of the Taichi programming language in computer graphics to molecular simulation education and research
To achieve interactive, real-time particle-based simulations accelerated by GPUs
To provide a platform for rapid implementation of novel simulation algorithms and machine-learned simulations

Examples

Molecular simulation examples

python run_examples.py [-h] example ensemble

positional arguments:

  example     [lj | mixlj | biglj | ho | chain | pr]
              lj: Lenneard-Jones system with 4096 molecules, in reduced units; 
              biglj: Lenneard-Jones system with 0.26 million molecules, in reduced units;
              mixlj: 3-component Lenneard-Jones mixture with 6000 molecules, in reduced units;
              ho: Harmonic oscillator around the center of the simulation box; 
              chain: 5 harmonic-bond chain molecules with 100 atoms each, bond bending and torsion not included, in real
              units
              pr: 512 propane molecules using the TraPPE-UA force field with a harmonic bond
              stretching potential at 423 K in a 50*50*50 angstrom box
  ensemble    [NVE | NVT] 
              NVE ensemble with Verlet integration or NVT ensemble with Nose-Hoover thermostat

optional arguments: -h, --help show help message and exit

Macroscopic simulation examples

mpm28.py: The MPM88 Taichi example (fluid simulation) in 3 dimensions. mpm48.py: The MPM99 Taichi example (fluid, jelly and snow) in 3 dimensions.

Graphics

TaichiMD ships with a miniature static version of taichi_three for rendering graphics, which requires the taichi_glsl package. If the renderer was not imported correctly, the example simulations will use the Taichi GUI canvas for graphics.

Possible extensions

Microscopic forces

Add support for torsional potentials as cosine series
Add Coulomb forces between charged atoms

Acceleration algorithms

Implement Ewald summation and/or fast multipole method for long-range forces (Coulomb)

Macroscopic forces

Implement gravity and wall boundaries
Incorporate macroscopic particle simulation algorithms (SPH, etc.)
Incorporate agent-based simulation algorithms (crowd simulation, particle swarm) and optimization-based integrators