  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
5-10x on two different systems equipped with NVIDIA K80 and V100 GPUs.
