Making Room for AI: Multi-GPU Molecular Dynamics with Deep Potentials in GROMACS
GROMACS is a de-facto standard for classical Molecular Dynamics (MD). The rise of AI-driven interatomic potentials that pursue near-quantum accuracy at MD throughput now poses a significant challenge: embedding neural-network inference into multi-GPU simulations retaining high-performance. In this work, we integrate the MLIP framework DeePMD-kit into GROMACS, enabling domain-decomposed, GPU-accelerated inference across multi-node systems. We extend the GROMACS NNPot interface with a DeePMD backend, and we introduce a domain decomposition layer decoupled from the main simulation. The inference is executed concurrently on all processes, with two MPI collectives used each step to broadcast c...
| Authors | Luca Pennati, Andong Hu, Ivy Peng et al. |
|---|---|
| Primary category | cs.DC |
| Published | 8 April 2026 |
| Last updated at source | 8 April 2026 |
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