GPU Acceleration of Multigrid Preconditioned Conjugate Gradient Solver on Block-Structured Cartesian Grid

Naoyuki Onodera, Yasuhiro Idomura, Yuta Hasegawa, Susumu Yamashita, Takashi Shimokawabe, Takayuki Aoki

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

5 Zitate (Scopus)

Abstract

We develop a multigrid preconditioned conjugate gradient (MG-CG) solver for the pressure Poisson equation in a two-phase flow CFD code JUPITER. The JUPITER code is redesigned to realize efficient CFD simulations including complex boundaries and objects based on a block-structured Cartesian grid system. The code is written in CUDA, and is tuned to achieve high performance on GPU based supercomputers. The main kernels of the MG-CG solver achieve more than 90% of the roofline performance.The MG preconditioner is constructed based on the geometric MG method with a three-stage V-cycle, and a red-black SOR (RB-SOR) smoother and its variant with cache-reuse optimization (CR-SOR) are applied at each stage. The numerical experiments are conducted for two-phase flows in a fuel bundle ofa nuclear reactor. Thanks to the block-structured data format, grids inside fuel pins are removed without performance degradation, and the total number of grids is reduced to 2.26 × 109, whichis about 70% of the original Cartesian grid. The MG-CG solvers with the RB-SOR and CR-SOR smoothersreduce the number of iterations to less than 15% and 9% of the original preconditioned CG method, leading to 3.1- and 5.9-times speedups, respectively. In the strong scaling test, the MG-CG solver with the CR-SOR smoother is accelerated by 2.1 times between 64 and 256 GPUs. The obtained performance indicates that the MG-CG solver designed for the block-structured grid is highly efficient and enables large-scale simulations of two-phase flows on GPU based supercomputers.

OriginalspracheEnglisch
TitelProceedings of International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2021
Herausgeber (Verlag)Association for Computing Machinery
Seiten120-128
Seitenumfang9
ISBN (elektronisch)9781450388429
DOIs
PublikationsstatusVeröffentlicht - 20 Jan. 2021
Extern publiziertJa
Veranstaltung2021 International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2021 - Virtual, Online, Südkorea
Dauer: 20 Jan. 202122 Jan. 2021

Publikationsreihe

NameACM International Conference Proceeding Series

Konferenz

Konferenz2021 International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2021
Land/GebietSüdkorea
OrtVirtual, Online
Zeitraum20/01/2122/01/21

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