Parallelizing and Balancing Coupled DSMC/PIC for Large-scale Particle Simulations

In high-performance and parallel computing, an important application class is particle simulation. Due to massive particle migration among distributed simulation workers across simulation iterations, achieving balanced runtime work distribution is vital for accelerating large-scale realistic particle simulations. This paper proposes a novel approach to enable dynamic load balance for distributed numerical particle simulations, specifically targeting the latest coupled DSMC/PI C method. Unlike prior work, our approach adopts a dual, nested unstructured grid organization to facilitate coupled DSMC/PIC computation and runtime grid distribution. Our implementation leverages both centralized and distributed communication strategies to dynamically migrate particles among arbitrary parallel processes. It then employs a load balancer - driven by a carefully designed analytical model and a grid remapping mechanism - to dynamically redistribute the simulation workloads among parallel simulation workers. By constantly monitoring and redis-tributing the simulation work across workers, our approach can adapt to the change of particle distribution across simulation iterations, avoiding a few workers becoming the performance bottleneck of the entire simulation process. We integrate our techniques into a coupled DSMC/PIC solver and apply them to simulate the plasma plume with hydrogen atoms and ions. Experimental results show that our approach can scale well up to 1500+ processes with billions of particles, exhibiting the state-of-the-art parallel simulation scalability and efficiency for plasma plume simulation.