The Communication-Overlapped Hybrid Decomposition Parallel Algorithm for Multi-Scale Fluid Simulations

Abstract

The MCDPar (Parallel algorithm for multi-scale simulations based on Mesh and BCF Decomposition) algorithm significantly reduced the execution time and improved the parallel scalability for the multi-scale fluid simulations. However, the performance bottleneck still exists for extremely large-scale parallel simulations. In this paper, we designed a communication-overlapped hybrid decomposition parallel algorithm to improve the performance of the original MCDPar on large-scale clusters. Through non-blocking communication and code scheduling, the communication overhead between the master and slave groups have been overlapped with the computation of more microscopic configuration fields for the master process. Thus the parallel efficiency and scalability of the multi-scale solver could be improved on large-scale parallel simulations. In the test case with the number of configuration fields NBCF = 1000 and mesh cells Ncell = 64000, the communication percentage between the corresponding master and slave processes is reduced by 39.71%. In the test case with NBCF = 3000 and Ncell = 64000, the time cost of the fastest execution is reduced by 31.13% using the communication-overlapped algorithm, which offers a better parallel scaling on 256 cores compared to original 128 cores.