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This paper introduces a framework for solving alternating current optimal power flow (ACOPF) problems using graphics processing units (GPUs). While GPUs have demonstrated remarkable performance in various computing domains, their…

Optimization and Control · Mathematics 2026-05-11 Sungho Shin , François Pacaud , Mihai Anitescu

We present the extension of the Tinker-HP package (Lagard\`ere et al., Chem. Sci., 2018,9, 956-972) to the use of Graphics Processing Unit (GPU) cards to accelerate molecular dynamics simulations using polarizable many-body force fields.…

The phase-field method has become a useful tool for the simulation of classical metallurgical phase transformations as well as other phenomena related to materials science. The thermodynamic consistency that forms the basis of these…

Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little…

Computational Physics · Physics 2013-08-26 Joshua A. Anderson , Eric Jankowski , Thomas L. Grubb , Michael Engel , Sharon C. Glotzer

Graphics Processing Units (GPUs) are high performance co-processors originally intended to improve the use and quality of computer graphics applications. Once, researchers and practitioners noticed the potential of using GPU for general…

Numerical Analysis · Computer Science 2016-07-12 K. Parand , Saeed Zafarvahedian , Sayyed A. Hossayni

Parallel algorithms on CPU and GPU are implemented for the Unified Gas-Kinetic Scheme and their performances are investigated and compared by a two dimensional channel flow case. The parallel CPU algorithm has a one dimensional block…

Computational Physics · Physics 2018-11-02 Jizhou Liu , Fang Q. Hu , Xiaodong Li

We present an implementation of phaseless Auxiliary-Field Quantum Monte Carlo (ph-AFQMC) utilizing graphical processing units (GPUs). The AFQMC method is recast in terms of matrix operations which are spread across thousands of processing…

Computational Physics · Physics 2018-09-07 James Shee , Evan J. Arthur , Shiwei Zhang , David R. Reichman , Richard A. Friesner

Finite element schemes based on discontinuous Galerkin methods possess features amenable to massively parallel computing accelerated with general purpose graphics processing units (GPUs). However, the computational performance of such…

Computational Physics · Physics 2016-04-20 Axel Modave , Amik St-Cyr , Tim Warburton

Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the…

We employ the Partially Saturated Cells Method (PSM) to model the interaction between the fluid flow and solid moving objects as an extension to the conventional lattice Boltzmann method. We introduce an efficient and accurate method for…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-28 P. Suffa , S. Kemmler , H. Koestler , U. Ruede

Finite element analysis of solid mechanics is a foundational tool of modern engineering, with low-order finite element methods and assembled sparse matrices representing the industry standard for implicit analysis. We use performance models…

Phase-field models are widely employed to simulate microstructure evolution during processes such as solidification or heat treatment. The resulting partial differential equations, often strongly coupled together, may be solved by a broad…

Materials Science · Physics 2023-06-23 A. D. Boccardo , M. Tong , S. B. Leen , D. Tourret , J. Segurado

The recently developed energy conserving semi-implicit method (ECsim) for PIC simulation is applied to multiple scale problems where the electron-scale physics needs to be only partially retained and the interest is on the macroscopic or…

Computational Physics · Physics 2017-05-24 Giovanni Lapenta , Diego Gonzalez-Herrero , Elisabetta Boella

We propose a spectral Particle-In-Cell (PIC) algorithm that is based on the combination of a Hankel transform and a Fourier transform. For physical problems that have close-to-cylindrical symmetry, this algorithm can be much faster than…

Plasma Physics · Physics 2016-05-04 Remi Lehe , Manuel Kirchen , Igor A. Andriyash , Brendan B. Godfrey , Jean-Luc Vay

We present a hybrid quantum-classical electrostatic Particle-in-Cell (PIC) method, where the electrostatic field Poisson solver is implemented on a quantum computer simulator using a hybrid classical-quantum Neural Network (HNN) using…

Particle-in-cell (PIC) simulations with Monte-Carlo collisions are used in plasma science to explore a variety of kinetic effects. One major problem is the long run-time of such simulations. Even on modern computer systems, PIC codes take a…

The Kernel Polynomial Method (KPM) is one of the fast diagonalization methods used for simulations of quantum systems in research fields of condensed matter physics and chemistry. The algorithm has a difficulty to be parallelized on a…

Computational Physics · Physics 2011-05-30 Shixun Zhang , Shinichi Yamagiwa , Masahiko Okumura , Seiji Yunoki

Recent developments in high peak-power table-top laser systems reaching highly relativistic light intensities have led to significant advances in laser-driven particle acceleration schemes (mainly the laser wakefield acceleration, LWFA)…

Plasma Physics · Physics 2026-05-13 Szilárd Majorosi , Nasr A. M. Hafz , Zsolt Lécz

A high-performance implementation of a multiphase lattice Boltzmann method based on the conservative Allen-Cahn model supporting high-density ratios and high Reynolds numbers is presented. Metaprogramming techniques are used to generate…

Fluid Dynamics · Physics 2020-12-14 Markus Holzer , Martin Bauer , Ulrich Rüde

Three-dimensional neutron transport calculations using the Method of Characteristics (MOC) are highly regarded for their exceptional computational efficiency, precision, and stability. Nevertheless, when dealing with extensive-scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-25 Faguo Zhou , Shunde Li , Rong Xue , Lingkun Bu , Ningming Nie , Peng Shi , Jue Wang , Yun Hu , Zongguo Wang , Yangang Wang , Qinmeng Yang , Miao Yu
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