arXiv subjects

Berk Hess

Publications and source records attributed to Berk Hess.

15 recordsLinked to original sources

arXiv2026

Malleable Molecular Dynamics Simulations with GROMACS and DMR

Static resource allocations in high-performance computing (HPC) lead to inefficiencies for time-varying workloads, causing idle resources, queue delays, and higher node-hour costs. The Dynamic Management of Resources (DMR) middleware enables MPI process malleability in Slurm via a simple API decoupled from scheduler internals. In this work, we integrate DMR into the GROMACS molecular dynamics engine to obtain a malleable variant that can dynamically adapt its MPI process count by combining communication-efficiency-aware reconfiguration with GROMACS' native checkpoint/restart mechanism. We evaluate this design on the MareNostrum~5 supercomputer, comparing dynamic runs against static executions and quantifying reconfiguration overheads, time-to-solution, and node-hour savings for bursty GROMACS workloads.

cs.DC↗

arXiv2026

Cahn-Hilliard Phase Field modelling captures nanoscale contact line dynamics on high-friction surfaces

Incorporating molecular-scale effects in the description of contact line motion is essential for accurately capturing all sources of energy dissipation in wetting dynamics. This holds particularly true in the cases where contact line friction dominates, and hydrodynamics models struggle to achieve regularisation due to the negligible Navier slip. We perform Molecular Dynamics simulations of water/hexane biphasic systems in a two-phase Couette flow configuration. Wetting occurs over a silica-like surface with controllable wettability. The simulation results are reproduced by a Phase Field model (Cahn-Hilliard Navier-Stokes equations), which includes localised contact line slip and contact angle dynamics. The continuous equations are directly parametrized from Molecular Dynamics simulation results, under the numerical sharp interface limit. We demonstrate that the Phase Field model can quantitatively reproduce Molecular Dynamics through a systematic calibration protocol. Critically, we show that contact line friction is the primary physical parameter requiring empirical calibration based on Molecular Dynamics data. Once extracted by matching contact angle dynamics, quantitative agreement across multiple observables is obtained, including interface curvature, steady contact line displacement, and the structure of streamlines. All other model parameters are determined a posteriori, according to the calculation of independent observables and under numerical constraints. The results presented in this article indicate that Phase Field modelling can capture the net effect of molecular processes on the mobility of contact lines and that the careful calibration of contact line friction based on the reconstruction of contact angle dynamics and interface bending is key to fully reconcile continuous models with Molecular Dynamics.

physics.flu-dyn↗

arXiv2026

Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS

Neural network potentials (NNPs) are rapidly changing the landscape of state-of-the-art molecular dynamics (MD) simulations. To make full use of this development, the community needs flexible, easy-to-use interfaces firmly integrated with existing methodologies. To address this, we here present an interface for hybrid machine learning/molecular mechanics (ML/MM) simulations implemented in the widely used MD code GROMACS. The interface enables NNPs trained in the PyTorch framework to contribute energies and forces during MD simulations, either for selected subsets or entire molecular systems. By defining a flexible set of model inputs and outputs, the interface is agnostic to specific NNP architectures and can accommodate a wide range of descriptor-based and message-passing models. In particular, the design integrates NNP inference seamlessly into the extensive GROMACS molecular simulation ecosystem, providing users with the capability to straightforwardly combine NNPs with existing advanced sampling and free energy workflows. We demonstrate the capabilities of the interface using several representative applications, including enhanced sampling of peptide torsional free energy landscapes, absolute solvation free energy calculations, and protein--ligand simulations. We also run performance benchmarks on water boxes for several different NNP architectures. Our interface is available in recent GROMACS releases, and we believe it will provide a practical foundation for incorporating machine learning potentials into production MD simulations of biomolecular systems.

physics.comp-ph↗

arXiv2023

Near-wall depletion and layering affect contact line friction of multicomponent liquids

The main causes of energy dissipation in micro- and nano-scale wetting are viscosity and liquid-solid friction localized in the three-phase contact line region. Theoretical models predict the contactline friction coefficient to correlate with the shear viscosity of the wetting fluid. Experiments conducted to investigate such correlation have not singled out a unique scaling law between the two coefficients. We perform Molecular Dynamics simulations of liquid water-glycerol droplets wetting silica-like surfaces, aimed to demystify the effect of viscosity on contact line friction. The viscosity of the fluid is tuned by changing the relative mass fraction of glycerol in the mixture and it is estimated both via equilibrium and non-equilibrium Molecular Dynamics simulations. Contact line friction is measured directly by inspecting the velocity of the moving contact line and the microscopic contact angle. It is found that the scaling between contact line friction and viscosity is sub-linear, contrary to the prediction of Molecular Kinetic Theory. The disagreement is explained by accounting for the depletion of glycerol in the near-wall region. A correction is proposed, based on multicomponent Molecular Kinetic Theory and the definition of a re-scaled interfacial friction coefficient.

physics.flu-dyn↗

arXiv2022

Asymmetry of wetting and de-wetting on high-friction surfaces originates from the same molecular physics

The motion of three-phase contact lines is one of the most relevant research topics of micro- and nano-fluidics. According to many hydrodynamic and molecular models, the dynamics of contact lines is assumed overdamped and dominated by localised liquid-solid friction, entailing the existence of a mobility relation between contact line speed and microscopic contact angle. We present and discuss a set of non-equilibrium atomistic Molecular Dynamics simulations of water nanodroplets spreading on or confined between silica-like walls, showing the existence of the aforementioned relation and its invariance under wetting modes (`spontaneous' or `forced'). Upon changing the wettability of the walls, it has been noticed that more hydrophilic substrates are easier to wet rather than de-wet; we show how this asymmetry can be automatically captured by a contact line friction model that accounts for the molecular transport between liquid layers. A simple examination of the order and orientation of near-contact-line water molecules corroborates the physical foundation of the model. Lastly, we propose an approach to discriminate between contact line friction models which overcomes the limitations of experimental resolution. This work constitutes a stepping stone towards demystifying wetting dynamics on high-friction hydrophilic substrates and underlines the relevance of contact line friction in modelling the motion of three-phase contact lines.

physics.flu-dyn↗

arXiv2022

Nanoscale sheared droplet: Volume-of-Fluid, phase-field and no-slip molecular dynamics

The motion of the three-phase contact line between two immiscible fluids and a solid surface arises in a variety of wetting phenomena and technological applications. One challenge in continuum theory is the effective representation of molecular phenomena close to the contact line. Here, we characterize the molecular processes of the moving contact line to assess the accuracy of two different continuum two-phase models. Specifically, molecular dynamics (MD) simulations of a two-dimensional droplet between two moving plates are used to create reference data for different capillary numbers and contact angles. We use a simple-point-charge/extended (SPC/E) water model with particle-mesh Ewald electrostatics treatment. This model provides a very small slip and a more realistic representation of the molecular physics than Lennards-Jones models. The Cahn-Hilliard phase-field model and the Volume-of-Fluid model are calibrated against the drop displacement from MD reference data. It is demonstrated that the calibrated continuum models can accurately capture droplet displacement and droplet breakup for different capillary numbers and contact angles. However, we also observe differences between continuum and atomistic simulations in describing the transient and unsteady droplet behavior, in particular, close to dynamical wetting transitions. The molecular dynamics of the sheared droplet provide insight of the line friction experienced by the advancing and receding contact lines and evidence of large-scale temporal "stick-slip" like oscillations. The presented results will serve as a stepping stone towards developing accurate continuum models for nanoscale hydrodynamics.

physics.flu-dyn↗

arXiv2020

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

The introduction of accelerator devices such as graphics processing units (GPUs) has had profound impact on molecular dynamics simulations and has enabled order-of-magnitude performance advances using commodity hardware. To fully reap these benefits, it has been necessary to reformulate some of the most fundamental algorithms, including the Verlet list, pair searching and cut-offs. Here, we present the heterogeneous parallelization and acceleration design of molecular dynamics implemented in the GROMACS codebase over the last decade. The setup involves a general cluster-based approach to pair lists and non-bonded pair interactions that utilizes both GPUs and CPU SIMD acceleration efficiently, including the ability to load-balance tasks between CPUs and GPUs. The algorithm work efficiency is tuned for each type of hardware, and to use accelerators more efficiently we introduce dual pair lists with rolling pruning updates. Combined with new direct GPU-GPU communication as well as GPU integration, this enables excellent performance from single GPU simulations through strong scaling across multiple GPUs and efficient multi-node parallelization.

physics.comp-ph↗

arXiv2020

Electrowetting diminishes contact line friction in molecular wetting

We use large-scale molecular dynamics to study dynamics at the three-phase contact line in electrowetting of water and electrolytes on no-slip substrates. Under the applied electrostatic potential the line friction at the contact line is diminished. The effect is consistent for droplets of different sizes as well as for both pure water and electrolyte solution droplets. We analyze the electric field at the contact line to show how it assists ions and dipolar molecules to advance the contact line. Without an electric field, the interaction between a substrate and a liquid has a very short range, mostly affecting the bottom, immobilized layer of liquid molecules which leads to high friction since mobile molecules are not pulled towards the surface. In electrowetting, the electric field attracts charged and polar molecules over a longer range which diminishes the friction.

physics.flu-dyn↗

arXiv2020

Steady moving contact line of water over a no-slip substrate

The movement of the triple contact line plays a crucial role in many applications such as ink-jet printing, liquid coating and drainage (imbibition) in porous media. To design accurate computational tools for these applications, predictive models of the moving contact line are needed. However, the basic mechanisms responsible for movement of the triple contact line are not well understood but still debated. We investigate the movement of the contact line between water, vapour and a silica-like solid surface under steady conditions in low capillary number regime. We use molecular dynamics (MD) with an atomistic water model to simulate a nanoscopic drop between two moving plates. We include hydrogen bonding between the water molecules and the solid substrate, which leads to a sub-molecular slip length. We benchmark two continuum methods, the Cahn-Hilliard phase-field (PF) model and a volume-of-fluid (VOF) model, against MD results. We show that both continuum models can reproduce the statistical measures obtained from MD reasonably well, with a trade-off in accuracy. We demonstrate the importance of the phase field mobility parameter and the local slip length in accurately modelling the moving contact line.

physics.flu-dyn↗

arXiv2018

Riemann metric approach to optimal sampling of multidimensional free-energy landscapes

Exploring the free-energy landscape along reaction coordinates or system parameters $λ$ is central to many studies of high-dimensional model systems in physics, e.g. large molecules or spin glasses. In simulations this usually requires sampling conformational transitions or phase transitions, but efficient sampling is often difficult to attain due to the roughness of the energy landscape. For Boltzmann distributions, crossing rates decrease exponentially with free-energy barrier heights. Thus, exponential acceleration can be achieved in simulations by applying an artificial bias along $λ$ tuned such that a flat target distribution is obtained. A flat distribution is however an ambiguous concept unless a proper metric is used, and is generally suboptimal. Here we propose a multidimensional Riemann metric, which takes the local diffusion into account, and redefine uniform sampling such that it is invariant under nonlinear coordinate transformations. We use the metric in combination with the accelerated weight histogram method, a free-energy calculation and sampling method, to adaptively optimize sampling toward the target distribution prescribed by the metric. We demonstrate that for complex problems, such as molecular dynamics simulations of DNA base-pair opening, sampling uniformly according to the metric, which can be calculated without significant computational overhead, improves sampling efficiency by 50-70%.

cond-mat.stat-mech↗

arXiv2018

Molecular Origin of Contact Line Friction in Dynamic Wetting

A hydrophilic liquid, such as water, forms hydrogen bonds with a hydrophilic substrate. The strength and locality of the hydrogen bonding interactions prohibit slip of the liquid over the substrate. The question then arises how the contact line can advance during wetting. Using large-scale molecular dynamics simulations we show that the contact line advances by single molecules moving ahead of the contact line through two distinct processes: either moving over or displacing other liquid molecules. In both processes friction occurs at the molecular scale. We measure the energy dissipation at the contact line and show that it is of the same magnitude as the dissipation in the bulk of a droplet. The friction increases significantly as the contact angle decreases, which suggests suggests thermal activation plays a role. We provide a simple model that is consistent with the observations.

physics.flu-dyn↗

arXiv2017

A comparison of the Spectral Ewald and Smooth Particle Mesh Ewald methods in GROMACS

The smooth particle mesh Ewald (SPME) method is an FFT based method for the fast evaluation of electrostatic interactions under periodic boundary conditions. A highly optimized implementation of this method is available in GROMACS, a widely used software for molecular dynamics simulations. In this article, we compare a more recent method from the same family of methods, the spectral Ewald (SE) method, to the SPME method in terms of performance and efficiency. We consider serial and parallel implementations of both methods for single and multiple core computations on a desktop machine as well as the Beskow supercomputer at KTH Royal Institute of Technology. The implementation of the SE method has been well optimized, however not yet comparable to the level of the SPME implementation that has been improved upon for many years. We show that the SE method is very efficient whenever used to achieve high accuracy and that it already at this level of optimization can be competitive for low accuracy demands.

math.NA↗

arXiv2015

Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS

GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.

cs.CE↗

arXiv2014

Accelerated weight histogram method for exploring free energy landscapes

Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A major advantage of the method is its general formulation, making it a powerful platform for developing further extensions and analyzing its relation to already existing methods. Here, we demonstrate its efficiency and general applicability by calculating the potential of mean force along a reaction coordinate for both a single dimension and multiple dimensions. We make use of a non-uniform, free energy dependent target distribution in reaction coordinate space so that computational efforts are not wasted on physically irrelevant regions. We present numerical results for molecular dynamics simulations of lithium acetate in solution and chignolin, a 10-residue long peptide that folds into a $β$-hairpin. We further present practical guidelines for setting up and running an AWH simulation.

physics.chem-ph↗

arXiv2013

A flexible algorithm for calculating pair interactions on SIMD architectures

Calculating interactions or correlations between pairs of particles is typically the most time-consuming task in particle simulation or correlation analysis. Straightforward implementations using a double loop over particle pairs have traditionally worked well, especially since compilers usually do a good job of unrolling the inner loop. In order to reach high performance on modern CPU and accelerator architectures, single-instruction multiple-data (SIMD) parallelization has become essential. Avoiding memory bottlenecks is also increasingly important and requires reducing the ratio of memory to arithmetic operations. Moreover, when pairs only interact within a certain cut-off distance, good SIMD utilization can only be achieved by reordering input and output data, which quickly becomes a limiting factor. Here we present an algorithm for SIMD parallelization based on grouping a fixed number of particles, e.g. 2, 4, or 8, into spatial clusters. Calculating all interactions between particles in a pair of such clusters improves data reuse compared to the traditional scheme and results in a more efficient SIMD parallelization. Adjusting the cluster size allows the algorithm to map to SIMD units of various widths. This flexibility not only enables fast and efficient implementation on current CPUs and accelerator architectures like GPUs or Intel MIC, but it also makes the algorithm future-proof. We present the algorithm with an application to molecular dynamics simulations, where we can also make use of the effective buffering the method introduces.

physics.comp-ph↗