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A novel parallelization paradigm has been developed for multi-GPU architectures. Classical multi-GPU parallelization for SPH rely on domain decomposition. In our approach each particle can be assigned to a GPU independently of its position…

Computational Physics · Physics 2023-10-06 Thomas Unfer , Anthony Collé , Jérôme Limido

As renewable energy integration, sector coupling, and spatiotemporal detail increase, energy system optimization models grow in size and complexity, often pushing solvers to their performance limits. This systematic review explores…

A phaser is an expressive synchronization construct that unifies collective and point-to-point coordination with dynamic task parallelism. Each task can participate in a phaser as a signaler, a waiter, or both. The participants in a phaser…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-15 Sri Raj Paul , Karthik Murthy , Kuldeep S. Meel , John Mellor-Crummey

This study addresses the challenge of simulating realistic particle systems by proposing a novel particle decomposition scheme that improves the parallel performance of surface resolved particle simulations. Realistic particle systems often…

Fluid Dynamics · Physics 2024-03-21 J. E. Marquardt , N. Hafen , M. J. Krause

This paper presents a comparative analysis of distributed training strategies for large-scale neural networks, focusing on data parallelism, model parallelism, and hybrid approaches. We evaluate these strategies on image classification…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-01 Vishnu Vardhan Baligodugula , Fathi Amsaad

We study parallel algorithms for the minimization of Deterministic Finite Automata (DFAs). In particular, we implement four different massively parallel algorithms on Graphics Processing Units (GPUs). Our results confirm the expectations…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-31 Jan Martens , Anton Wijs

Furthering our understanding of many of today's interesting problems in plasma physics---including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects---requires large-scale kinetic…

Computational Physics · Physics 2020-10-28 Kyle G. Miller , Roman P. Lee , Adam Tableman , Anton Helm , Ricardo A. Fonseca , Viktor K. Decyk , Warren B. Mori

We develop a novel parallel resampling algorithm for fully parallelized particle filters, which is designed with GPUs (graphics processing units) or similar parallel computing devices in mind. With our new algorithm, a full cycle of…

Computation · Statistics 2016-08-17 Kenichiro McAlinn , Teruo Nakatsuma

In this talk I discuss the general question of the portability of Molecular Dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision arithmetics of the today available APE platforms does…

Biological Physics · Physics 2009-10-30 G. La Penna , S. Letardi , V. Minicozzi , S. Morante , G. C. Rossi , G. Salina

Compactly expressing large-scale datasets through Multivariate Functional Approximations (MFA) can be critically important for analysis and visualization to drive scientific discovery. Tackling such problems requires scalable data…

Numerical Analysis · Mathematics 2022-10-14 Vijay S. Mahadevan , David Lenz , Iulian Grindeanu , Thomas Peterka

Diffusion models have achieved remarkable progress in high-fidelity image, video, and audio generation, yet inference remains computationally expensive. Nevertheless, current diffusion acceleration methods based on distributed parallelism…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Euisoo Jung , Byunghyun Kim , Hyunjin Kim , Seonghye Cho , Jae-Gil Lee

Current algorithms for large-scale industrial optimization problems typically face a trade-off: they either require exponential time to reach optimal solutions, or employ problem-specific heuristics. To overcome these limitations, we…

Quantum Physics · Physics 2025-10-16 Matteo Vandelli , Francesco Ferrari , Daniele Dragoni

Many parallel algorithms use at least linear auxiliary space in the size of the input to enable computations to be done independently without conflicts. Unfortunately, this extra space can be prohibitive for memory-limited machines,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-02 Yan Gu , Omar Obeya , Julian Shun

System performance for networks composed of interconnected subsystems can be increased if the traditionally separated subsystems are jointly optimized. Recently, parallel and distributed optimization methods have emerged as a powerful tool…

Optimization and Control · Mathematics 2013-02-14 Ion Necoara , Valentin Nedelcu , Ioan Dumitrache

This paper presents PipeFusion, an innovative parallel methodology to tackle the high latency issues associated with generating high-resolution images using diffusion transformers (DiTs) models. PipeFusion partitions images into patches and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Jiarui Fang , Jinzhe Pan , Aoyu Li , Xibo Sun , Jiannan Wang

This paper presents our work on developing parallel computational methods for two-phase flow on modern parallel computers, where techniques for linear solvers and nonlinear methods are studied and the standard and inexact Newton methods are…

Computational Engineering, Finance, and Science · Computer Science 2017-01-24 Hui Liu , Lihua Shen , Yan Chen , Kun Wang , Bo Yang , Zhangxin Chen

This paper describes the parallel implementation of the TRANSIMS traffic micro-simulation. The parallelization method is domain decomposition, which means that each CPU of the parallel computer is responsible for a different geographical…

Computational Engineering, Finance, and Science · Computer Science 2016-08-31 Kai Nagel , Marcus Rickert

Particle-In-Cell codes are widely used for plasma physics simulations. It is often the case that particles within a computational cell need to be split to improve the statistics or, in the case of non-uniform meshes, to avoid the…

Computational Physics · Physics 2021-04-22 Roch Smets , Nicolas Aunais , ANdrea Ciardi , Matthieu Drouin , Martin Campos-Pino , Philip Deegan

A novel parallel technique for Fourier-Galerkin pseudo-spectral methods with applications to two-dimensional Navier-Stokes equations and inviscid Boussinesq approximation equations is presented. It takes the advantage of the programming…

Computational Physics · Physics 2009-11-10 Z. Yin , Li Yuan , Tao Tang

We discuss the parallelization of algorithms for solving polynomial systems symbolically by way of triangular decomposition. Algorithms for solving polynomial systems combine low-level routines for performing arithmetic operations on…

Symbolic Computation · Computer Science 2019-06-04 Mohammadali Asadi , Alexander Brandt , Robert H. C. Moir , Marc Moreno Maza , Yuzhen Xie