iPIC3D is a widely used massively parallel Particle-in-Cell code for the simulation of space plasmas. However, its current implementation does not support execution on multiple GPUs. In this paper, we describe the porting of iPIC3D particle mover to GPUs and the optimization steps to increase the performance and parallel scaling on multiple GPUs. We analyze the strong scaling of the mover on two GPU clusters and evaluate its performance and acceleration. The optimized GPU version which uses pinned memory and asynchronous data prefetching outperform their corresponding CPU versions by 5−10× on two different systems equipped with NVIDIA K80 and V100 GPUs.

We perform and analyze global Particle-in-Cell (PIC) simulations of the interaction between solar wind and an outgassing comet with the goal of studying the plasma kinetic dynamics of a cometary environment. To achieve this, we design and implement a new numerical method in the iPIC3D code to model outgassing from the comet: new plasma particles are ejected from the comet” surface” at each computational cycle. Our simulations show that a bow shock is formed as a result of the interaction between solar wind and outgassed particles. The analysis of distribution functions for the PIC simulations shows that at the bow shock part of the incoming solar wind, ions are reflected while electrons are heated. This work attempts to reveal kinetic effects in the atmosphere of an outgassing comet using a fully kinetic Particle-in-Cell model.

A three-dimensional implicit particle-in-cell (iPIC3D) method implemented by S. Markidis et. al. in [“Multiscale simulations of plasma with iPIC3D”, Mathematics and Computers in Simulation, 80(2010), 1509-1519] allows time steps at magnetohy- drodynamics time scale. The code requires the solution of two linear systems: a Poisson system related to divergence cleaning, and a system related to a second order formulation of Maxwell equation. In iPIC3D, the former is the most costly.