电子与封装2026，Vol.26Issue(1)：68-77,10.DOI:10.16257/j.cnki.1681-1070.2026.0011
扩散模型神经网络加速策略综述
Review of Neural Network Acceleration Strategies for Diffusion Models
摘要
Abstract
With the development of neural networks,diffusion models have achieved remarkable success in image generation tasks due to their unique diffusion mechanism.However,to achieve outstanding task performance,they introduce substantial computational overheads and complex network structures,which severely hinders their widespread application,particularly on edge devices with limited resources.High-efficiency model acceleration algorithms and hardware-software co-design frameworks for accelerators have emerged as effective solutions.Based on various diffusion model acceleration and efficient deployment strategies,an overview of state-of-the-art acceleration techniques for diffusion models is provided,covering both high-efficiency algorithmic designs for general-purpose computing platforms and hardware-software framework co-designs.关键词
扩散模型/模型加速/边缘部署/软硬件协同设计/高效推理Key words
diffusion model/model acceleration/edge deployment/hardware-software co-design/efficient inference分类
信息技术与安全科学引用本文复制引用
邹子涵,闫鑫明,郑鹏,张顺,蔡浩,刘波..扩散模型神经网络加速策略综述[J].电子与封装,2026,26(1):68-77,10.基金项目
国家重点研发计划(2023YFB4403103) （2023YFB4403103）
