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Aiming to accelerate the training of large deep neural networks (DNN) in an energy-efficient way, analog in-memory computing (AIMC) emerges as a solution with immense potential. AIMC accelerator keeps model weights in memory without moving…

Machine Learning · Computer Science 2026-04-28 Zhaoxian Wu , Quan Xiao , Tayfun Gokmen , Hsinyu Tsai , Kaoutar El Maghraoui , Tianyi Chen

Massively parallel computer architectures create new opportunities for the performance of long-timescale molecular dynamics (MD) simulations. Here, we introduce the path-accelerated molecular dynamics (PAMD) method that takes advantage of…

Computational Physics · Physics 2021-01-11 Jorge L. Rosa-Raíces , Bin Zhang , Thomas F. Miller

Molecular Dynamics (MD) simulation is a powerful tool for understanding the dynamics and structure of matter. Since the resolution of MD is atomic-scale, achieving long time-scale simulations with femtosecond integration is very expensive.…

Machine Learning · Computer Science 2022-04-27 Zijie Li , Kazem Meidani , Prakarsh Yadav , Amir Barati Farimani

Understanding the complex behavior of molecular systems is fundamental to fields such as physics, materials science, and biology. Molecular dynamics (MD) simulations are crucial tools for studying atomic-level dynamics. This work focuses on…

Computational Engineering, Finance, and Science · Computer Science 2025-07-16 David Martin , Samuel James Newcome , Markus Mühlhäußer , Manish Kumar Mishra , Fabio Alexander Gratl , Hans-Joachim Bungartz

Path integral Monte Carlo (PIMC) and path integral molecular dynamics (PIMD) provide the golden standard for the ab initio simulations of identical particles. In this work, we achieved significant GPU acceleration based on PIMD, which is…

Computational Physics · Physics 2026-03-31 Yunuo Xiong

Molecular dynamics (MD) simulation is one of the past decade's most important tools for enabling biology scientists and researchers to explore human health and diseases. However, due to the computation complexity of the MD algorithm, it…

Computational Physics · Physics 2016-11-15 Jason Cong , Zhenman Fang , Hassan Kianinejad , Peng Wei

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modelling of such systems.…

Soft Condensed Matter · Physics 2007-05-23 Michael Patra , Marja T. Hyvonen , Emma Falck , Mohsen Sabouri-Ghomi , Ilpo Vattulainen , Mikko Karttunen

Large-scale molecular dynamics simulations with high accuracy have been increasingly popular for their capability to bridge the gap between atomistic modeling and mesoscale phenomena. Both machine learning potentials and enhanced sampling…

Computational Physics · Physics 2026-03-24 Haoting Zhang , Qiuhan Jia , Zhennan Zhang , Yijie Zhu , Zhongwei Zhang , Junjie Wang , Jiuyang Shi , Zheyong Fan , Jian Sun

Molecular dynamics (MD) simulations provide detailed insight into atomic-scale mechanisms but are inherently restricted to small spatio-temporal scales. Coarse-grained molecular dynamics (CGMD) techniques allow simulations of much larger…

Computational Physics · Physics 2025-02-10 Yangshuai Wang , Gabor Csanyi , Christoph Ortner

Developing efficient path integral (PI) methods for atomistic simulations of vibrational spectra in heterogeneous condensed phases and interfaces has long been a challenging task. Here, we present the h-CMD method, short for hybrid centroid…

Chemical Physics · Physics 2025-05-08 Dil K. Limbu , Nathan London , Md Omar Faruque , Mohammad R. Momeni

Quantum-based molecular dynamics (QMD) is a highly accurate and transferable method for material science simulations. However, the time scales and system sizes accessible to QMD are typically limited to picoseconds and a few hundred atoms.…

Accelerated molecular dynamics (MD) simulations are implemented to model the sliding process of AFM experiments at speeds close to those found in experiment. In this study the hyperdynamics method, originally devised to extend MD time…

Materials Science · Physics 2015-05-14 Woo Kyun Kim , Michael L. Falk

Analog in-memory computing (AIMC) cores offers significant performance and energy benefits for neural network inference with respect to digital logic (e.g., CPUs). AIMCs accelerate matrix-vector multiplications, which dominate these…

Multiple time-scale algorithms exploit the natural separation of time-scales in chemical systems to greatly accelerate the efficiency of molecular dynamics simulations. Although the utility of these methods in systems where the interactions…

Computational Physics · Physics 2015-06-18 Nathan Luehr , Thomas E. Markland , Todd J. Martinez

The two main thrusts of computational science are more accurate predictions and faster calculations; to this end, the zeitgeist in molecular dynamics (MD) simulations is pursuing machine learned and data driven interatomic models, e.g.…

Computational Physics · Physics 2020-02-24 Saaketh Desai , Samuel Temple Reeve , James F. Belak

For nearly the past 30 years, Centroid Molecular Dynamics (CMD) has proven to be a viable classical-like phase space formulation for the calculation of quantum dynamical properties. However, calculation of the centroid effective force…

Chemical Physics · Physics 2022-09-15 Timothy D. Loose , Patrick G. Sahrmann , Gregory A. Voth

Molecular simulations of the forced unfolding and refolding of biomolecules or molecular complexes allow to gain important kinetic, structural and thermodynamic information about the folding process and the underlying energy landscape. In…

Soft Condensed Matter · Physics 2021-05-26 Marco Oestereich , Jürgen Gauss , Gregor Diezemann

A hierarchical parallelization has been implemented in a new unified code PIMD-SMASH for ab initio simulation where the replicas and the Born-Oppenheimer forces are parallelized. It is demonstrated that ab initio path integral molecular…

Chemical Physics · Physics 2016-02-17 Sergi Ruiz-Barragan , Kazuya Ishimura , Motoyuki Shiga

Accurate calculations of molecular crystals are crucial for drug design and crystal engineering. However, periodic high-level density functional calculations using hybrid functionals are often prohibitively expensive for relevant systems.…

Chemical Physics · Physics 2024-01-23 Johannes Hoja , Alexander List , A. Daniel Boese

We present a new method, called SISYPHUS (Stochastic Iterations to Strengthen Yield of Path Hopping over Upper States), for extending accessible time-scales in atomistic simulations. The method proceeds by separating phase space into…

Materials Science · Physics 2015-03-12 Pratyush Tiwary , Axel van de Walle