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GPU并行计算驱动的大规模无人机集群仿真研究

余玲 郭川东 王国庆 刘艳菊 曹立佳

计算机工程与应用2025,Vol.61Issue(22):114-122,9.
计算机工程与应用2025,Vol.61Issue(22):114-122,9.DOI:10.3778/j.issn.1002-8331.2505-0315

GPU并行计算驱动的大规模无人机集群仿真研究

Research on Large-Scale Unmanned Aerial Vehicle Swarms Simulation Driven by GPU Parallel Computing

余玲 1郭川东 2王国庆 3刘艳菊 2曹立佳2

作者信息

  • 1. 四川轻化工大学 计算机科学与工程学院,四川 宜宾 644000
  • 2. 四川轻化工大学 自动化与信息工程学院,四川 宜宾 644000||智能感知与控制四川省重点实验室,四川 宜宾 644000||企业信息化与物联网测控技术四川省高校重点实验室,四川 宜宾 644000
  • 3. 四川轻化工大学 自动化与信息工程学院,四川 宜宾 644000
  • 折叠

摘要

Abstract

With the continuous expansion of unmanned aerial vehicle(UAV)swarm simulation scales,traditional CPU-based serial computing methods have become increasingly inadequate in meeting the high-efficiency,real-time,and low-cost requirements of large-scale simulations.To address this challenge,this paper proposes a GPU-parallel-computing-driven method for large-scale UAV swarm simulation.From a methodological perspective,a parallel simulation frame-work compatible with GPU execution characteristics is systematically developed.Leveraging CUDA as the foundation for parallel computation,the method exploits the inherent independence of simulation objects by adopting a fine-grained data-parallel strategy.Simulation tasks are evenly distributed across parallel threads based on a static load-balancing principle and thread mapping model,thereby maximizing computational resource utilization.To validate the effectiveness of the proposed method,a parallel simulation system for large-scale UAV swarms is constructed,and performance benchmarking against conventional CPU-based simulation approaches is conducted.The evaluation is systematically performed from two critical dimensions:simulation real-time performance and system scalability.Experimental results demonstrate that while ensuring simulation accuracy and system stability,this method can achieve real-time simulation of up to 2 322 drone mod-els on an NVIDIA GeForce GTX 1650 graphics card.This work provides a practical solution for efficient UAV swarm simulation and offers valuable technical insights for addressing large-scale parallel computing challenges in other domains.

关键词

GPU计算/无人机集群/并行仿真/实时性

Key words

GPU computing/UAV swarm/parallel simulation/real-time capability

分类

计算机与自动化

引用本文复制引用

余玲,郭川东,王国庆,刘艳菊,曹立佳..GPU并行计算驱动的大规模无人机集群仿真研究[J].计算机工程与应用,2025,61(22):114-122,9.

基金项目

四川省科技计划(2024NSFSC2048) (2024NSFSC2048)

四川轻化工大学科研创新团队计划(SUSE652A011). (SUSE652A011)

计算机工程与应用

OA北大核心

1002-8331

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