Author(s)

Zhicong Liu^1,2, Ji Qiang^1*

¹Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
²Key Laboratory of Particle Acceleration Physics and Technology, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.

Particle accelerators play an important role in a wide range of scientific discoveries and industrial applications. The self-consistent multi-particle simulation based on the particle-in-cell (PIC) method has been used to study charged particle beam dynamics inside those accelerators. However, the PIC simulation is time-consuming and needs to use modern parallel computers for high-resolution applications. In this paper, we implemented a parallel beam dynamics PIC code on multi-node hybrid architecture computers with multiple Graphics Processing Units (GPUs). We used two methods to parallelize the PIC code on multiple GPUs and observed that the replication method is a better choice for moderate problem size and current computer hardware while the domain decomposition method might be a better choice for large problem size and more advanced computer hardware that allows direct communications among multiple GPUs. Using the multi-node hybrid architectures at Oak Ridge Leadership Computing Facility (OLCF), the optimized GPU PIC code achieves a reasonable parallel performance and scales up to 64 GPUs with 16 million particles.

Particle Accelerator, Particle-In-Cell, GPU, Parallel Beam Dynamics Simulation

Liu, Z. and Qiang, J. (2019) Implementation of a Particle Accelerator Beam Dynamics Code on Multi-Node GPUs. Journal of Software Engineering and Applications, 12, 321-338. doi: 10.4236/jsea.2019.129020.