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Related Experiment Video

Updated: Dec 13, 2025

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field.

Xiaohua Zhang1, Shiv Sundram2, Tomas Oppelstrup1

  • 1Physical and Life Sciences (PLS) Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, USA.

The Journal of Chemical Physics
|August 6, 2020
PubMed
Summary
This summary is machine-generated.

We optimized molecular dynamics simulations using the Martini force field on graphics processing units (GPUs), achieving a 278-fold speedup. This enhancement accelerates complex simulations for scientific discovery.

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Area of Science:

  • Computational Chemistry
  • Molecular Dynamics
  • Scientific Computing

Background:

  • Molecular dynamics simulations are crucial for understanding molecular behavior.
  • The Martini force field is widely used for coarse-grained simulations.
  • Accelerating simulations is essential for tackling larger and more complex systems.

Purpose of the Study:

  • To implement the Martini force field and simulation integration steps on graphics processing units (GPUs).
  • To enhance the performance of the ddcMD molecular dynamics program.
  • To enable faster and more efficient molecular simulations.

Main Methods:

  • Porting the Martini force field to a heterogeneous programming model for GPU acceleration.
  • Implementing the entire integration step (thermostat, barostat, constraint solver) on GPUs.
  • Benchmarking the ddcMD program against GROMACS for Martini simulations.

Main Results:

  • Achieved a 278-fold speedup using one GPU compared to one CPU core.
  • Demonstrated performance of 1.04 µs/day on one NVIDIA V100 GPU for a 136k particle system.
  • Attained an aggregate performance of 6.19 µs/day on one Summit node with six GPUs.
  • Offloaded all computations to the GPU, requiring only one CPU core for I/O management.

Conclusions:

  • The GPU implementation in ddcMD significantly accelerates molecular dynamics simulations.
  • This advancement allows for more complex simulations and frees up CPU resources.
  • The open-source ddcMD code is available for broader scientific use.