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We present an efficient open-source implementation of the multiparticle collision dynamics (MPCD) algorithm that scales to run on hundreds of graphics processing units (GPUs). We especially focus on optimizations for modern GPU…

Soft Condensed Matter · Physics 2018-08-01 Michael P. Howard , Athanassios Z. Panagiotopoulos , Arash Nikoubashman

The moment-of-fluid method (MOF) is known as an extension of the volume-of-fluid method with piecewise linear interface construction (VOF-PLIC). In this study, several directional splitting advection algorithms are extended from the…

Numerical Analysis · Mathematics 2021-08-13 Zhoueng Ye

The Mancha3D code is a versatile tool for numerical simulations of magnetohydrodynamic processes in solar/stellar atmospheres. The code includes non-ideal physics derived from plasma partial ionization, a realistic equation of state and…

We present a novel method of magnetohydrodynamics (MHD) within the smoothed particle hydrodynamics scheme using the Geometric Density average force expression (GDSPH). GDSPH has recently been shown to reduce the leading order errors and…

Instrumentation and Methods for Astrophysics · Physics 2020-07-31 Robert Wissing , Sijing Shen

To date, fully cosmological hydrodynamic disk simulations to redshift zero have only been undertaken with particle-based codes, such as GADGET, Gasoline, or GCD+. In light of the (supposed) limitations of traditional implementations of…

We describe the implementation of the shearing box approximation for the study of the dynamics of accretion disks in the Athena magnetohydrodynamics (MHD) code. Second-order Crank-Nicholson time differencing is used for the Coriolis and…

Instrumentation and Methods for Astrophysics · Physics 2015-05-19 James M. Stone , Thomas A. Gardiner

Modern GPUs are equipped with large amounts of high-bandwidth memory, enabling them to support mini-batch sizes of up to tens of thousands of training samples. However, most existing optimizers struggle to perform effectively at such a…

Machine Learning · Computer Science 2026-02-10 Yishun Lu , Wesley Armour

Smoothed Particle Hydrodynamics (SPH) is essential for modeling complex large-deformation problems across various applications, requiring significant computational power. A major portion of SPH computation time is dedicated to the Nearest…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-23 Zirui Mao , Xinyi Li , Shenyang Hu , Ganesh Gopalakrishnan , Ang Li

The challenge to fully exploit the potential of existing and upcoming scientific instruments like large single-dish radio telescopes is to process the collected massive data effectively and efficiently. As a "quasi 2D stencil computation"…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-07-12 Hao Wang , Ce Yu , Jian Xiao , Shanjiang Tang , Min Long , Ming Zhu

A data-driven and equation-free approach is proposed and discussed to model ships maneuvers in waves, based on the dynamic mode decomposition (DMD). DMD is a dimensionality-reduction/reduced-order modeling method, which provides a linear…

Dynamical Systems · Mathematics 2021-05-28 Matteo Diez , Andea Serani , Emilio F. Campana , Frederick Stern

We introduce the Mechanic, a new open-source code framework. It is designed to reduce the development effort of scientific applications by providing unified API (Application Programming Interface) for configuration, data storage and task…

Instrumentation and Methods for Astrophysics · Physics 2015-06-18 Mariusz Słonina , Krzysztof Goździewski , Cezary Migaszewski

This paper describes ZEUS-MP, a multi-physics, massively parallel, message- passing implementation of the ZEUS code. ZEUS-MP differs significantly from the ZEUS-2D code, the ZEUS-3D code, and an early "version 1" of ZEUS-MP distributed…

Cosmological simulations require the use of a multiple time-stepping scheme. Without such a scheme, cosmological simulations would be impossible due to their high level of dynamic range; over eleven orders of magnitude in density. Such a…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-05 Josh Borrow , Richard G. Bower , Peter W. Draper , Pedro Gonnet , Matthieu Schaller

Developing an efficient code for large, multiscale astrophysical simulations is crucial in preparing the upcoming era of exascale computing. RAMSES is an astrophysical simulation code that employs parallel processing based on the Message…

Instrumentation and Methods for Astrophysics · Physics 2024-11-25 San Han , Yohan Dubois , Jaehyun Lee , Juhan Kim , Corentin Cadiou , Sukyoung K. Yi

Elastic filaments are vital to biological, physical and engineering systems, from cilia driving fluid in the lungs to artificial swimmers and micro-robotics. Simulating slender structures requires intricate balance of elastic, body, active,…

Biological Physics · Physics 2023-06-02 Paul Fuchter , Hermes Bloomfield-Gadêlha

Machine learning has recently made significant strides in reducing design cycle time for complex products. Ship design, which currently involves years long cycles and small batch production, could greatly benefit from these advancements. By…

Machine Learning · Computer Science 2023-05-18 Noah J. Bagazinski , Faez Ahmed

A weighted residual collocation methodology for simulating two-dimensional shear-driven and natural convection flows has been presented. Using a dyadic mesh refinement, the methodology generates a basis and a multiresolution scheme to…

Fluid Dynamics · Physics 2020-07-23 Jahrul Alam , Raymond Walsh , Alamgir Hossain , Andrew Rose

The main features of a three dimensional, high-resolution special relativistic hydro code based on relativistic Riemann solvers are described. The capabilities and performance of the code are discussed. In particular, we present the results…

Astrophysics · Physics 2009-10-31 M. A. Aloy , J. M. Ibanez , J. M. Marti , E. Muller

High-energy astrophysical systems and compact objects are frequently modeled using ideal relativistic magnetohydrodynamic (MHD) or force-free electrodynamic (FFE) simulations, with the underlying assumption that the discretisation from the…

High Energy Astrophysical Phenomena · Physics 2025-09-25 Michael P. Grehan , Tanisha Ghosal , James R. Beattie , Bart Ripperda , Oliver Porth , Fabio Bacchini

Modern machine learning systems operating in dynamic environments often face \textit{sequential covariate shift} (SCS), where input distributions evolve over time while the conditional distribution remains stable. We introduce FADE…

Machine Learning · Computer Science 2025-07-28 Behraj Khan , Tahir Qasim Syed , Nouman Muhammad Durrani