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The Smoothed Particles Hydrodynamics (SPH) is a particle-based, meshfree, Lagrangian method used to simulate multidimensional fluids with arbitrary geometries, most commonly employed in astrophysics, cosmology, and computational…

Computational Engineering, Finance, and Science · Computer Science 2022-12-21 Aurélien Cavelan , Rubén M. Cabezón , Michal Grabarczyk , Florina M. Ciorba

In the paper we discuss the main features of the software package for numerical simulations of the surface water dynamics. We consider an approximation of the shallow water equations together with the parallel technologies for NVIDIA CUDA…

Computational Engineering, Finance, and Science · Computer Science 2017-05-03 Tatyana Dyakonova , Alexander Khoperskov , Sergey Khrapov

This study presents a GPU-accelerated, fully coupled fluid-solid-thermal Smoothed Particle Hydrodynamics (SPH) framework for high-fidelity analysis of splash-lubricated gearboxes. A series of thermo-fluid simulations of a bevel-helical gear…

Fluid Dynamics · Physics 2025-12-11 Yongchuan Yu , Dong Wu , Oskar J. Haidn , Xiangyu Hu

The use of adaptive spatial resolution to simulate flows of practical interest using Smoothed Particle Hydrodynamics (SPH) is of considerable importance. Recently, Muta and Ramachandran [1] have proposed an efficient adaptive SPH method…

Fluid Dynamics · Physics 2022-05-17 Asmelash Haftu , Abhinav Muta , Prabhu Ramachandran

Magnetohydrodynamic (MHD) simulations based on the ideal MHD equations have become a powerful tool for modeling phenomena in a wide range of applications including laboratory, astrophysical, and space plasmas. In general, high-resolution…

Computational Physics · Physics 2010-11-23 Hon-Cheng Wong , Un-Hong Wong , Xueshang Feng , Zesheng Tang

We present diffSPH, a novel open-source differentiable Smoothed Particle Hydrodynamics (SPH) framework developed entirely in PyTorch with GPU acceleration. diffSPH is designed centrally around differentiation to facilitate optimization and…

Fluid Dynamics · Physics 2025-07-30 Rene Winchenbach , Nils Thuerey

We present results based on an implementation of the Godunov Smoothed Particle Hydrodynamics (GSPH), originally developed by Inutsuka (2002), in the GADGET-3 hydrodynamic code. We first review the derivation of the GSPH discretization of…

Instrumentation and Methods for Astrophysics · Physics 2015-05-28 Giuseppe Murante , Stefano Borgani , Riccardo Brunino , Suneg-Hoon Cha

In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-10-19 I. Zacharoudiou , J. W. S. McCullough , P. V. Coveney

Smoothed particle hydrodynamics (SPH) is omnipresent in modern engineering and scientific disciplines. SPH is a class of Lagrangian schemes that discretize fluid dynamics via finite material points that are tracked through the evolving…

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

This paper presents the implementation of a HLLC finite volume solver using GPU technology for the solution of shallow water problems in two dimensions. It compares both CPU and GPU approaches for implementing all the solver's steps. The…

Computational Engineering, Finance, and Science · Computer Science 2018-07-03 Fabrice Zaoui

Mesoscopic simulations of hydrocarbon flow in source shales are challenging, in part due to the heterogeneous shale pores with sizes ranging from a few nanometers to a few micrometers. Additionally, the sub-continuum fluid-fluid and…

Computational Physics · Physics 2019-09-13 Yidong Xia , Ansel Blumers , Zhen Li , Lixiang Luo , Yu-Hang Tang , Joshua Kane , Hai Huang , Matthew Andrew , Milind Deo , Jan Goral

Computational fluid dynamics is a crucial tool to theoretically explore the cosmos. In the last decade, we have seen a substantial methodological diversification with a number of cross-fertilizations between originally different methods.…

Instrumentation and Methods for Astrophysics · Physics 2023-01-25 Stephan Rosswog

The recent trend of using Graphics Processing Units (GPU's) for high performance computations is driven by the high ratio of price performance for these units, complemented by their cost effectiveness. At first glance, computational fluid…

Computational Engineering, Finance, and Science · Computer Science 2018-02-13 Kiril S. Shterev

We present an efficient implementation for running three-dimensional numerical simulations of fluid-structure interaction problems on single GPUs, based on Nvidia CUDA through Numba and Python. The incompressible flow around moving bodies…

Fluid Dynamics · Physics 2024-12-05 M. Guerrero-Hurtado , J. M. Catalán , M. Moriche , A. Gonzalo , O. Flores

This paper introduces open-source computational fluid dynamics software named open computational fluid dynamic code for scientific computation with graphics processing unit (GPU) system (OpenCFD-SCU), developed by the authors for direct…

Fluid Dynamics · Physics 2022-12-21 Guanlin Dang , Shiwei Liu , Tongbiao Guo , Junyi Duan , Xinliang Li

We present LBcuda, a GPU accelerated version of LBsoft, our open-source MPI-based software for the simulation of multi-component colloidal flows. We describe the design principles, the optimization and the resulting performance as compared…

The last decade has seen a shift in the computer systems industry where heterogeneous computing has become prevalent. Graphics Processing Units (GPUs) are now present in supercomputers to mobile phones and tablets. GPUs are used for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-04 Yehia Arafa , Abdel-Hameed Badawy , Gopinath Chennupati , Nandakishore Santhi , Stephan Eidenbenz

Geometric Semantic Genetic Programming (GSGP) is a state-of-the-art machine learning method based on evolutionary computation. GSGP performs search operations directly at the level of program semantics, which can be done more efficiently…

Neural and Evolutionary Computing · Computer Science 2021-06-09 Leonardo Trujillo , Jose Manuel Muñoz Contreras , Daniel E Hernandez , Mauro Castelli , Juan J Tapia

The unavailability of accurate boundary treatment methods for compressible Smoothed Particle Hydrodynamics (SPH) severely limits its ability to simulate flows in and around bodies. To this end, challenges specific to compressible flows with…

Fluid Dynamics · Physics 2024-08-27 Navaneet Villodi , Prabhu Ramachandran