中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Symplectic multi-particle tracking on GPUs

文献类型:期刊论文

作者Liu, ZC; Qiang, J; Liu ZC(刘志聪)
刊名COMPUTER PHYSICS COMMUNICATIONS
出版日期2018
卷号226页码:10-17
关键词Particle accelerator Symplectic Multi-particle tracking GPU
ISSN号0010-4655
DOI10.1016/j.cpc.2018.02.001
文献子类Article
英文摘要A symplectic multi-particle tracking model is implemented on the Graphic Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) language. The symplectic tracking model can preserve phase space structure and reduce non-physical effects in long term simulation, which is important for beam property evaluation in particle accelerators. Though this model is computationally expensive, it is very suitable for parallelization and can be accelerated significantly by using GPUs. In this paper, we optimized the implementation of the symplectic tracking model on both single GPU and multiple GPUs. Using a single GPU processor, the code achieves a factor of 2-10 speedup for a range of problem sizes compared with the time on a single state-of-the-art Central Processing Unit (CPU) node with similar power consumption and semiconductor technology. It also shows good scalability on a multi-GPU cluster at Oak Ridge Leadership Computing Facility. In an application to beam dynamics simulation, the GPU implementation helps save more than a factor of two total computing time in comparison to the CPU implementation. Published by Elsevier B.V.
电子版国际标准刊号1879-2944
WOS关键词IN-CELL CODE ; PARTICLE ; ACCELERATORS ; SIMULATIONS ; INTEGRATION
WOS研究方向Computer Science ; Physics
语种英语
WOS记录号WOS:000428483000002
源URL[http://ir.ihep.ac.cn/handle/311005/285780]  
专题高能物理研究所_加速器中心
作者单位中国科学院高能物理研究所
推荐引用方式
GB/T 7714
Liu, ZC,Qiang, J,Liu ZC. Symplectic multi-particle tracking on GPUs[J]. COMPUTER PHYSICS COMMUNICATIONS,2018,226:10-17.
APA Liu, ZC,Qiang, J,&刘志聪.(2018).Symplectic multi-particle tracking on GPUs.COMPUTER PHYSICS COMMUNICATIONS,226,10-17.
MLA Liu, ZC,et al."Symplectic multi-particle tracking on GPUs".COMPUTER PHYSICS COMMUNICATIONS 226(2018):10-17.

入库方式: OAI收割

来源:高能物理研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。