# Extreme scaling of the metadynamics of paths algorithm on the pre-exascale JUWELS Booster supercomputer

Source: [Extreme scaling of the metadynamics of paths algorithm on the pre-exascale JUWELS Booster supercomputer](<https://www.sota2.com/research/paper/68fa4acb1e209131ce941353>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T08:00:44.461Z

Authors: Nitin Malapally, Marta Devodier, Giulia Rossetti, Paolo Carloni, Davide Mandelli

Published: 2025-01-21T08:17:39.000Z

## Abstract

Molecular dynamics (MD)-based path sampling algorithms are a very important class of methods used to study the energetics and kinetics of rare (bio)molecular events. They sample the highly informative but highly unlikely reactive trajectories connecting different metastable states of complex (bio)molecular systems. The metadynamics of paths (MoP) method proposed by Mandelli, Hirshberg, and Parrinello \[Pys. Rev. Lett. 125 2, 026001 (2020)\] is based on the Onsager-Machlup path integral formalism. This provides an analytical expression for the probability of sampling stochastic trajectories of given duration. In practice, the method samples reactive paths via metadynamics simulations performed directly in the phase space of all possible trajectories. Its parallel implementation is in principle infinitely scalable, allowing arbitrarily long trajectories to be simulated. Paving the way for future applications to study the thermodynamics and kinetics of protein-ligand (un)binding, a problem of great pharmaceutical interest, we present here the efficient implementation of MoP in the HPC-oriented biomolecular simulation software GROMACS. Our benchmarks on a membrane protein (150,000 atoms) show an unprecedented weak scaling parallel efficiency of over 70% up to 3200 GPUs on the pre-exascale JUWELS Booster machine at the J\\"ulich Supercomputing Center.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2501.11962>)

[PDF](<https://arxiv.org/pdf/2501.11962.pdf>)