## 1 Introduction  
With the development of the supercomputer theory and computer hardware technology, numerical computation has become an important technical mechanism in scientific work. Computational fluid dynamics (CFD) is a significant research field. Among the many numerical methods in the CFD field, the lattice Boltzmann method (LBM) [1,2] is a numerical simulation method with great potential. It is derived from a lattice gas automaton, which is based on the microscopic thermal motion in fluid molecules. The statistical average describes mesoscopically the macroscopic motion of the fluid. The method treats fluid as a mass of small particles with only the mass and no volume. These small particles move on a regular grid, collide with surrounding particles, and transfer statistical data. The movement of a large number of particles helps in obtaining macroscopic properties of the fluid, such as density, velocity, and pressure. The collision migration idea of LBM elementary particles, and the use of Cartesian mesh division, enable simple boundary condition processing and natural parallelism, which is suitable for large-scale numerical computation on the supercomputer [3]. [PERSON] et al. presented a novel multi-physics coupled algorithm based on the LBM, which employs an Eulerian description of fluid and ions, combined with a Lagrangian representation of moving charged particles, and achieved excellent performance and scaling on up to 65,536 cores of a current supercomputer [4]. For large-scale grids, [PERSON] et al. discussed modeling and computational aspects of their approach, and presented computational results, including experimental validations [5]. [PERSON] et al. introduced the lattice Boltzmann benchmark kernels, a suite for benchmarking simple LBM kernels, which may be used for performance experiments or can act as a blueprint for an implementation [6]. [PERSON] et al. analyzed the performance and energy to solution properties of a lattice Boltzmann flow solver on the chip and highly parallel levels for an Intel Sandy Bridge (SNB) EP (Xeon E5-2680)-based system [7]. [PERSON] et al. introduced a decomposition approach for generic three-dimensional (3D) stencil problems with formulations for calculating dynamically copied position indexes, subdomain addresses, subdomain size, and halo cells, and the new pipelined 3D LBM code outperforms the original OpenCL version by 33%, by overlapping computation and communication [8]. [PERSON] et al. proposed a new robust algorithm to automatically generate hierarchical Cartesian meshes on distributed multi-core HPC(High Performance Computing) systems with multiple levels of refinement [9]. [PERSON] et al. proposed an effective approach to accelerate the LBM computing by fully exploiting temporal locality on a shared memory multi-core platform [10]. The supercomputer research community of China is already ranked among the top in the world. China's supercomputer has ranked first in the TOP500 ranking 10 consecutive times, from June 2013 to November 2017. In the TOP500 list in November 2018, China's Sunway TaihuLight and Tianhe-2A supercomputers ranked third and fourth, respectively [11]. Sunway TaihuLight is also the first system with a peak performance of more than 100 PFlops in the world. It uses the SW26010 many-core processor, which contains a management processing element (MPE) and 64 computing processing elements (CPEs)--a core-group (CG)--and one node has four CGs, totaling 260 processing units. The Sunway TaihuLight has a total of 40,960 SW26010 processors with superior computing power. Based on the Sunway TaihuLight, \"10M-core scalable fully-implicit solver for nonhydrostatic atmospheric dynamics\" and \"nonlinear earthquake simulation on Sunway TaihuLight\" won the highest award in the field of high-performance computing--the Gordon Bell Award [12]--in 2016 and 2017. In terms of aeronautical-engineering computations, the wing is the main device for generating lift. Its structure is complex, and has become the focus of research [13; 14].