Suppr超能文献

加速静电粒子模拟:一种用于高效等离子体研究的新型基于 FPGA 的方法。

Accelerating electrostatic particle-in-cell simulation: A novel FPGA-based approach for efficient plasma investigations.

机构信息

Department of Electrical & Computer Engineering, Gulf University for Science & Technology, Hawally, Kuwait.

Department of Engineering Management, Gulf University for Science & Technology, Hawally, Kuwait.

出版信息

PLoS One. 2024 Jun 3;19(6):e0302578. doi: 10.1371/journal.pone.0302578. eCollection 2024.

Abstract

Particle-in-cell (PIC) simulation serves as a widely employed method for investigating plasma, a prevalent state of matter in the universe. This simulation approach is instrumental in exploring characteristics such as particle acceleration by turbulence and fluid, as well as delving into the properties of plasma at both the kinetic scale and macroscopic processes. However, the simulation itself imposes a significant computational burden. This research proposes a novel implementation approach to address the computationally intensive phase of the electrostatic PIC simulation, specifically the Particle-to-Interpolation phase. This is achieved by utilizing a high-speed Field Programmable Gate Array (FPGA) computation platform. The suggested approach incorporates various optimization techniques and diminishes memory access latency by leveraging the flexibility and performance attributes of the Intel FPGA device. The results obtained from our study highlight the effectiveness of the proposed design, showcasing the capability to execute hundreds of functional operations in each clock cycle. This stands in contrast to the limited operations performed in a general-purpose single-core computation platform (CPU). The suggested hardware approach is also scalable and can be deployed on more advanced FPGAs with higher capabilities, resulting in a significant improvement in performance.

摘要

粒子模拟(PIC)模拟是一种广泛应用于研究等离子体的方法,等离子体是宇宙中常见的物质状态。这种模拟方法对于探索由湍流和流体引起的粒子加速等特性,以及深入研究等离子体在动力学尺度和宏观过程中的性质非常有用。然而,模拟本身会带来很大的计算负担。本研究提出了一种新的实现方法来解决静电 PIC 模拟中计算密集的阶段,特别是粒子到插值阶段。这是通过利用高速现场可编程门阵列(FPGA)计算平台来实现的。所提出的方法结合了各种优化技术,并利用英特尔 FPGA 设备的灵活性和性能特性来减少内存访问延迟。我们的研究结果突出了所提出设计的有效性,展示了在每个时钟周期执行数百个功能操作的能力。这与在通用单核计算平台(CPU)中执行的有限操作形成对比。所提出的硬件方法也具有可扩展性,可以部署在具有更高能力的更先进的 FPGA 上,从而显著提高性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d40/11146701/a7b6c3452f36/pone.0302578.g001.jpg

相似文献

5
FPGA-Based Real-Time Simulation Platform for Large-Scale STN-GPe Network.基于 FPGA 的大规模 STN-GPe 网络实时仿真平台。
IEEE Trans Neural Syst Rehabil Eng. 2020 Nov;28(11):2537-2547. doi: 10.1109/TNSRE.2020.3027546. Epub 2020 Nov 6.
6
X-Ray Tomography Reconstruction Accelerated on FPGA Through High-Level Synthesis Tools.X 射线断层扫描重建在 FPGA 上通过高级综合工具加速。
IEEE Trans Biomed Circuits Syst. 2023 Apr;17(2):375-389. doi: 10.1109/TBCAS.2023.3258879. Epub 2023 May 10.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验