Streaming Molecular Dynamics Simulation Data for On-the-fly Processing and Analysis

Abstract

Only a small fraction of the data generated in state-of-the-art all-atom multi-microsecond molecular dynamics (MD) simulations is typically analyzed. With femtosecond integration steps, microsecond simulations generate billions of time steps containing atomic positions, velocities, and forces, often corresponding to petabytes of data. Since this exceeds practical storage capacities, only a subset of frames is usually written to trajectory files at intervals of 10-100 ps. While sufficient for ensemble averages and slow dynamics, this approach discards information on fast processes such as molecular vibrations, solvent dynamics, short-lived transition states, and transport phenomena that are directly related to macroscopic properties and experimental observables. Here, we introduce a streaming framework for MD simulations that provides direct access to all data generated during a running simulation. Instead of writing high-frequency output to disk, the framework enables user-defined analysis and processing routines to access simulation data in real time. To achieve this, we extend the Interactive Molecular Dynamics (IMD) protocol and implement an enhanced version, termed IMDv3, in the MD packages GROMACS, NAMD, and LAMMPS. We further introduce the Python package imdclient, which receives IMDv3 data streams and exposes them to external applications. To maximize usability, we add an imdclient-based reader to the MDAnalysis package, enabling streamed simulation data to be analyzed alongside conventional trajectory files. Benchmark results show that streaming can improve performance compared to simulations with high-frequency trajectory output. Example applications include live monitoring of custom variables, evaluation of velocity time-correlation functions with fast fluctuations, and real-time analysis of membrane pore currents.