GPIC: A set of high-efficiency CUDA Fortran code using gpu for particle-in-cell simulation in space physics

Qiyang Xiong, Shiyong Huang, Zhigang Yuan, Bharatkumar Sharma, Lvlin Kuang, Kui Jiang, Lin Yu

Abstract: Previous implementation of the full kinetic particle-in-cell (PIC) simulation on the Graphical Processing Unit (GPU) device has shown advantages compared to traditional Central Processing Unit (CPU) computing. However, conventional PIC simulations using GPU computing have faced limitations in terms of low performance when the simulation box size or the number of particles per cell increases. In this study, we boost computing efficiency by designing novel schemes of kernels with the combination of numerical and technical aspects. The time expenses of the global data transferring and duplicate data fetching processes have been massively reduced by the utilization of the on-chip memory. The reduction treatment on the particles, the graded current computing scheme, and the 2.5D thread launch strategy are designed to accelerate the simulation iterations. The new scheme can reach up to about 5.5 times the acceleration ratio than the old one and attain the highest to 734 times faster than the program using CPUs. Our new scheme can realize large-scale PIC simulations with both decent performances on the legacy GPUs and the increasing trend of the acceleration ratio on the lasted GPUs.