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
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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 |
DOI | 10.1016/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
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