Acceleration of the OpenFOAM-based MHD solver using graphics processing units

He, Qingyun; Chen, Hongli; Feng, Jianmei

doi:10.1016/j.fusengdes.2015.09.017

Cited by 14 publications

(5 citation statements)

References 14 publications

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“…Off-the-shelf software, such as commercial offerings from Ansys, Fluidyna, Simscale and many others arguably give the most productive approach to setting up and running CFD simulations, and they have been optimised extensively for CPUs, with certain modules offering GPU support as well. Open source packages such as OpenFOAM also give access to an array of features, though they tend to be less optimised and GPU support is sporadic [17,18], and generally not officially supported. These packages however limit the exploration of new algorithmic techniques and numerical methods, simply because either they are closed source, or they are difficult to modify -as such they lie outside the focus of our discussion in this paper.…”

Section: Classical Software Librariesmentioning

confidence: 99%

Productivity, performance, and portability for computational fluid dynamics applications

Reguly

Mudalige

2020

Computers & Fluids

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Hardware trends over the last decade show increasing complexity and heterogeneity in high performance computing architectures, which presents developers of CFD applications with three key challenges; the need for achieving good performance, being able to utilise current and future hardware by being portable, and doing so in a productive manner. These three appear to contradict each other when using traditional programming approaches, but in recent years, several strategies such as template libraries and Domain Specific Languages have emerged as a potential solution; by giving up generality and focusing on a narrower domain of problems, all three can be achieved. This paper gives an overview of the state-of-the-art for delivering performance, portability, and productivity to CFD applications, ranging from highlevel libraries that allow the symbolic description of PDEs to low-level techniques that target individual algorithmic patterns. We discuss advantages and challenges in using each approach, and review the performance benchmarking literature that compares implementations for hardware architectures and their programming methods, giving an overview of key applications and their comparative performance.

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Section: Classical Software Librariesmentioning

confidence: 99%

Productivity, performance, and portability for computational fluid dynamics applications

Reguly

Mudalige

2020

Computers & Fluids

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“…Qingyun He et al (He, Chen, and Feng 2015) Authors accelerated the MHD solver by replacing its linear system solvers since solving matrices occupy most of program running time. Also, authors replaced sparse matrix vector product (SMVP) kernels with the corresponding GPU implementations.…”

Section: Related Researchmentioning

confidence: 99%

OpenFOAM on GPUs using AMGX

2017

25th High Performance Computing Symposium (HPC 2017)

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Field Operation and Manipulation (OpenFOAM) is a free, open-source, feature-rich Computational Fluid Dynamics (CFD) software that is used to solve a variety of problems in continuum mechanics. Depending on the type of problem and required accuracy, an OpenFOAM simulation may take several weeks to complete. For sufficiently large simulations, linear solvers consume a large portion of the execution time. AmgX is a state of the art, high performance library which provides an elegant way to accelerate linear solvers on GPUs. AmgX library provides multi-grid solvers, Krylov methods, smoothers, support for block systems and MPI. In this work, we implemented OpenFOAM solvers on GPUs using the AmgX library. We also created helper functions which enable seamless integration of these solvers with OpenFOAM. These functions will take care of converting the linear system to AmgX's format and apply the user specified configurations to solve it. Experiments carried out using a wind rotor simulation and a fan wing simulation show that the use of AmgX library gives upto 10% speedup in the total simulation time and around 2x speedup in linear system solving portion within the simulation.

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“…Computational Fluid Dynamics (CFD) is one of the most time-consuming activities in High-Performance Computing (HPC). Recent research shows that heterogeneous architectures, with Graphics Processing Units (GPUs) as massively parallel co-processors to the Central Processing Unit (CPU), can accelerate computation processes in various CFD applications [1][2][3][4][5][6][7]. Developing a general-purpose CFD software to leverage this powerful hardware is challenging and time-intensive, as evidenced by the cited references.…”

Section: Introductionmentioning

confidence: 99%

Turbomachinery GPU Accelerated CFD: An Insight into Performance

Molinero-Hernández,

Galván-González,

Herrera-Sandoval

et al. 2024

Computation

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Driven by the emergence of Graphics Processing Units (GPUs), the solution of increasingly large and intricate numerical problems has become feasible. Yet, the integration of GPUs into Computational Fluid Dynamics (CFD) codes still presents a significant challenge. This study undertakes an evaluation of the computational performance of GPUs for CFD applications. Two Compute Unified Device Architecture (CUDA)-based implementations within the Open Field Operation and Manipulation (OpenFOAM) environment were employed for the numerical solution of a 3D Kaplan turbine draft tube workbench. A series of tests were conducted to assess the fixed-size grid problem speedup in accordance with Amdahl’s Law. Additionally, tests were performed to identify the optimal configuration utilizing various linear solvers, preconditioners, and smoothers, along with an analysis of memory usage.

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Acceleration of the OpenFOAM-based MHD solver using graphics processing units

Cited by 14 publications

References 14 publications

Productivity, performance, and portability for computational fluid dynamics applications

Productivity, performance, and portability for computational fluid dynamics applications

OpenFOAM on GPUs using AMGX

Turbomachinery GPU Accelerated CFD: An Insight into Performance

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