An Efficient GPU Parallelization for Arbitrary Collocated Polyhedral Finite Volume Grids and Its Application to Incompressible Fluid Flows

Jaiswal, Shashank; Reddy, Rajesh; Banerjee, Raja; Sato, Shingo; Komagata, Daisuke; Ando, Mitsuru; Okada, Jun

doi:10.1109/hipcw.2016.020

Cited by 3 publications

(1 citation statement)

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“…The study of methods to accelerate computation is a traditional subject in Computational Fluid Dynamics (CFD). Many research papers and articles have been published exploring the acceleration of various CFD solvers using GPUs [7,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. These papers often discuss implementing parallelization strategies, porting solvers to GPU architectures, and optimizing computation to take advantage of GPU capabilities.…”

Section: Introductionmentioning

confidence: 99%

GPU Acceleration of CFD Simulations in OpenFOAM

Piscaglia,

Ghioldi

2023

Aerospace

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We introduce algorithmic advancements designed to expedite simulations in OpenFOAM using GPUs. These developments include the following. (a) The amgx4Foam library, which connects the open-source AmgX library from NVIDIA to OpenFOAM. Matrix generation, involving tasks such numerical integration and assembly, is performed on CPUs. Subsequently, the assembled matrix is processed on the CPU. This approach accelerates the computationally intensive linear solver phase of simulations on GPUs. (b) Enhancements to code performance in reactive flow simulations, by relocating the solution of finite-rate chemistry to GPUs, which serve as co-processors. We present code verification and validation along with performance metrics targeting two distinct application sets, namely, aerodynamics calculations and supersonic combustion with finite-rate chemistry.

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