9:00 AM - 10:30 AM
[PEM17-P13] Performance Evaluation of Load-balanced Particle-based Plasma Kinetic Simulations
Keywords:plasma, numerical simulation, Particle-In-Cell method
We have recently developed a general dynamic load-balancing framework for particle-based kinetic simulations in C++. It is based on decomposing the computational domain into small chunks [e.g., Germaschewski et al., 2016, Derouillat et al., 2018, Rowan et al., 2021]. The load balancing is performed by distributing the chunks into MPI ranks so that each rank's computational load becomes equal as much as possible. Therefore, the chunk size and the number of chunks per MPI process are essential parameters controlling the efficiency of dynamic load balancing. Furthermore, it has been well-recognized that the chunk size also affects the single-core performance because a smaller chunk makes it possible to use CPU cash more efficiently.
The motivation of this work is to evaluate the performance of a standard PIC code built on top of the newly developed framework. We evaluate the load-balancing performance as a function of chunk size for problems with highly-inhomogeneous density, such as magnetic reconnection. Flat-MPI and OpenMP-MPI hybrid parallelization strategies will be tested on Intel Xeon and Fujitsu A64FX architectures. SIMD optimization and efficient cash usage may also be discussed.