Scaling and performance portability of the particle-in-cell scheme for plasma physics applications through mini-apps targeting exascale architectures^∗

We perform a scaling and performance portability study of the electrostatic particle-in-cell scheme for plasma physics applications through a set of mini-apps we name “Alpine”, which can make use of exascale computing capabilities. The mini-apps are based on IPPL, a framework that is designed around performance portable and dimensionality independent particles and fields. We benchmark the simulations with varying parameters, such as grid resolutions (512³ to 2048³) and number of simulation particles (10⁹ to 10¹¹), with the following mini-apps: weak and strong Landau damping, bump-on-tail and two-stream instabilities, and the dynamics of an electron bunch in a charge-neutral Penning trap. We show strong and weak scaling and analyze the performance of different components on several pre-exascale architectures, such as Piz-Daint, Cori, Summit, and Perlmutter. While the scaling and portability study helps to identify the performance critical components of the particle-in-cell scheme on the current state-of-the-art computing architectures, the mini-apps by themselves can be used to develop new algorithms and optimize their high performance implementations targeting exascale architectures.