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In order to run Computational Fluid Dynamics (CFD) codes on large scale infrastructures, parallel computing has to be used because of the computational intensive nature of the problems. In this paper we investigate the ADAPT platform where…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-25 Imad Kissami , Christophe Cerin , Fayssal Benkhaldoun , Gilles Scarella

Recent years have seen many successful applications of machine learning (ML) to facilitate fluid dynamic computations. As simulations grow, generating new training datasets for traditional offline learning creates I/O and storage…

Foundational models (FMs) have made significant strides in the healthcare domain. Yet the data silo challenge and privacy concern remain in healthcare systems, hindering safe medical data sharing and collaborative model development among…

Machine Learning · Computer Science 2025-02-27 Zheling Tan , Kexin Ding , Jin Gao , Mu Zhou , Dimitris Metaxas , Shaoting Zhang , Dequan Wang

The molecular dynamics simulation package GROMACS runs efficiently on a wide variety of hardware from commodity workstations to high performance computing clusters. Hardware features are well exploited with a combination of SIMD,…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-14 Carsten Kutzner , Szilárd Páll , Martin Fechner , Ansgar Esztermann , Bert L. de Groot , Helmut Grubmüller

Molecular dynamics (MD) simulates the time evolution of atomic systems governed by interatomic forces, and the fidelity of these simulations depends critically on the underlying force model. Classical force fields (CFFs) rely on fixed…

Performance · Computer Science 2026-03-05 Udari De Alwis , Benjamin E. Mayer , Tom J. Ashby , Maria Barrera , Timon Evenblij , Joyjit Kundu

In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's…

Robotics · Computer Science 2022-04-21 Adam Ligocki , Ales Jelinek , Ludek Zalud

Molecular dynamics (MD) simulations underpin modern computational drug discovery, materials science, and biochemistry. Recent machine learning models provide high-fidelity MD predictions without the need to repeatedly solve quantum…

Machine Learning · Computer Science 2026-04-24 Luke Thompson , Davy Guan , Dai Shi , Slade Matthews , Junbin Gao , Andi Han

As many robot automation applications increasingly rely on multi-core processing or deep-learning models, cloud computing is becoming an attractive and economically viable resource for systems that do not contain high computing power…

MuSim is a new user-friendly program designed to interface to many different particle simulation codes, regardless of their data formats or geometry descriptions. It presents the user with a compelling graphical user interface that includes…

We propose a method for multi-scale hybrid simulations of molecular dynamics (MD) and computational fluid dynamics (CFD). In the method, usual lattice-mesh based simulations are applied for CFD level, but each lattice is associated with a…

Soft Condensed Matter · Physics 2014-01-20 Shugo Yasuda , Ryoichi Yamamoto

We present a novel phase-field model development capability in the open source MOOSE finite element framework. This facility is based on the 'modular free energy' approach in which the phase-field equations are implemented in a general form…

Materials Science · Physics 2017-02-28 Daniel Schwen , Larry K. Aagesen , John W. Peterson , Michael R. Tonks

This paper introduces the first open-source FPGA-based infrastructure, MetaSys, with a prototype in a RISC-V core, to enable the rapid implementation and evaluation of a wide range of cross-layer techniques in real hardware.…

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…

Computational Physics · Physics 2026-04-24 Lukas Müllender , Berk Hess , Erik Lindahl

FOS, which means light in Greek, is an open-source program for Fast Optical Spectrum calculations of nanoparticle media. This program takes the material properties and a description of the system as input, and outputs the spectral response…

Computational Physics · Physics 2024-09-04 Daniel Carne , Joseph Peoples , Ziqi Guo , Dudong Feng , Zherui Han , Xiaojie Liu , Xiulin Ruan

The use of derivative-based solvers to compute solutions to optimal control problems with non-differentiable cost or dynamics often requires reformulations or relaxations that complicate the implementation or increase computational…

Optimization and Control · Mathematics 2021-10-12 Ian McInerney , Lucian Nita , Yuanbo Nie , Alberto Oliveri , Eric C. Kerrigan

Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes. Accurate MD simulations require computationally demanding quantum-mechanical calculations, being practically limited to short timescales…

With the continuous growth of processing power for scientific computing, first principles Born-Oppenheimer molecular dynamics (MD) simulations are becoming increasingly popular for the study of a wide range of problems in materials science,…

Materials Science · Physics 2015-06-04 Anders M. N. Niklasson , Marc J. Cawkwell

Evidence suggests that Free/Libre Open Source Software (FLOSS) environments provide unlimited learning opportunities. Community members engage in a number of activities both during their interaction with their peers and while making use of…

Software Engineering · Computer Science 2023-07-18 Patrick Mukala , Antonio Cerone , Franco Turini

Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of…

In our previous work, we demonstrated that it is feasible to perform analysis on mutation signature data without the need for downloads or installations and analyze individual patient data at scale without compromising privacy. Building on…