Towards a Peta-scale Unstructured Computational Fluid Dynamics (CFD) Acceleration Toolkit based on Sunway architectures?

Abstract

Adopting Large Eddy Simulation (LES) to simulate the complex flow is appropriate to overcome the limitation of current Reynolds-Averaged Navier-Stokes (RANS) modeling and it provides a deeper understanding of the complicated transitional and turbulent flow mechanism. However, the large computational cost limits its application in high Reynolds number flow. Though Sunway TaihuLight supercomputer has revealed its remarkable performance on atmospheric dynamics and earthquake simulation, there are still some unsolved problems for researchers: unstructured mesh and complicated programming pattern on SW26010. Therefore, we develop an ultra-scalable Unstructured Acceleration Toolkit (UNAT). In this toolkit, we derive a graph decomposition model of computing flow and reuse data through L1 cache to optimize the operator. Multi-level block method and register communication are developed to achieve the best performance of CPEs. CFD engineer can ignore the detail of parallel programming on SW26010 and utilize the operator interfaces offered by UNAT. Finally, we deploy UNAT to accelerate a combustion code and obtain 12-19x performance speed-up on specific operators, onto 65 cores within the chip compared with MPE.