关键词: 计算流体力学, 谱元法, 并行区域分解, 矩阵乘并行优化技术, 数值反应堆

Abstract: Thermal fluid simulation is an important part of the numerical reactor. High-precision large-scale numerical calculation is the basis for realizing high-fidelity numerical simulation. The use of computational fluid dynamics (CFD) software for high-precision and large-scale numerical simulation poses a huge challenge to computing resources and storage resources, and requires parallel implementation of supercomputers. The numerical method based on the spectral element method was taken to solve the N-S (Navier-Stokes) equation as the research object in the paper. Aiming at the two core problems of domain decomposition and parallel optimization of Chinese supercomputers based on the typical hybrid architecture, a hybrid parallel recursive spectral bisection method for massive fine meshes was proposed to achieve large-scale domain decomposition, and a set of applications centered on small matrix-matrix multiplication was established. The hybrid parallel large-scale domain decomposition method was tested on the Tianhe-2 Supercomputer. Compared with the serial domain decomposition module of the open source CFD software Nek5000, the performance is improved by about 95%. The small matrix-matrix multiplication optimization for SW26010 was tested on Sunway TaihuLight Supercomputing. When the order of the spectral element reaches 24, the performance is improved by about 51.9%. Both technologies were applied in the core software CVR-PACA of China Numerical Reactor.

Key words: computational fluid dynamics, spectral element method, parallel domain decomposition, matrix multiplication parallel optimization technique, numerical reactor