A Scheme of Full Kinetic Particle-in-cell Algorithms for GPU Acceleration Using CUDA Fortran Programming

Abstract

The emerging computable devices, graphical processing units (GPUs), are gradually applied in the simulations of space physics. In this paper, we introduce an approach that implements full kinetic particle-in-cell simulations on GPU architecture devices using the CUDA Fortran language programming for the first time. Using the latest high-performance computing NVIDIA GPUs, this program, which follows the second-order leap-frog iteration method, can speed up the computing process by a factor of 150–285 on a single device compared with the time cost of running with a single core of an Intel Xeon Gold processor. Our scheme improves fast accessibility to the simulation results and provides valuable assistance in studying the physical process.