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Title: Implementation of a Particle Accelerator Beam Dynamics Code on Multi-Node GPUs

Abstract

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.

Authors:
 [1];  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chinese Academy of Sciences, Beijing (China). Inst. of High Energy Physics, Key Lab. of Particle Acceleration Physics and Technology
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1570231
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Software Engineering and Applications
Additional Journal Information:
Journal Volume: 12; Journal Issue: 9; Journal ID: ISSN 1945-3116
Country of Publication:
United States
Language:
English
Subject:
43 PARTICLE ACCELERATORS; particle accelerator; Particle-In-Cell; GPU; parallel beam dynamics simulation

Citation Formats

Liu, Zhicong, and Qiang, Ji. Implementation of a Particle Accelerator Beam Dynamics Code on Multi-Node GPUs. United States: N. p., 2019. Web. doi:10.4236/jsea.2019.129020.
Liu, Zhicong, & Qiang, Ji. Implementation of a Particle Accelerator Beam Dynamics Code on Multi-Node GPUs. United States. doi:10.4236/jsea.2019.129020.
Liu, Zhicong, and Qiang, Ji. Wed . "Implementation of a Particle Accelerator Beam Dynamics Code on Multi-Node GPUs". United States. doi:10.4236/jsea.2019.129020. https://www.osti.gov/servlets/purl/1570231.
@article{osti_1570231,
title = {Implementation of a Particle Accelerator Beam Dynamics Code on Multi-Node GPUs},
author = {Liu, Zhicong and Qiang, Ji},
abstractNote = {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.},
doi = {10.4236/jsea.2019.129020},
journal = {Journal of Software Engineering and Applications},
issn = {1945-3116},
number = 9,
volume = 12,
place = {United States},
year = {2019},
month = {9}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Figure 1 Figure 1: A single step of the PIC model.

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