电子学报2024，Vol.52Issue(3)：872-884,13.DOI:10.12263/DZXB.20220106
MRNDA:一种基于资源受限片上网络的深度神经网络加速器组播机制研究
MRNDA:A Multicast Mechanism for Resource-Constrained Noc-Based Deep Neural Network Accelerators
摘要
Abstract
Network-on-Chip(NoC)devices have been widely used in multiprocessor systems.In recent years,NoC-based deep neural network(DNN)accelerators have been proposed to connect neural computing devices using NoCs.Such designs dramatically reduce off-chip memory accesses of these platforms thus reduce the accelerators'classification latency and power consumption.However,the large number of one-to-many packet transfers significantly increase the communica-tion latency with traditional unicast channels.We proposed a multicast mechanism for resource-constrained noc-based deep neural network accelerators(MRNDA)to compute large DNN models by using limited number of processor elements(PEs).This paper proposes a tree-based multicast acceleration network to decrease the communication latency of DNN ac-celerators.Simulation results show that,compared with the baseline method,the multicast mechanism proposed in this pa-per reduces the classification latency of the accelerator by up to 86.7%and the communication latency by up to 88.8%,while its router's area and power only account for 9.5%and 10.3%of the baseline routers.关键词
片上网络/深度神经网络加速器/组播/路由器架构/多物理网络Key words
network-on-chip/deep neural network accelerator/multicast/router architecture/multiple network分类
信息技术与安全科学引用本文复制引用
欧阳一鸣,王奇,汤飞扬,周武,李建华..MRNDA:一种基于资源受限片上网络的深度神经网络加速器组播机制研究[J].电子学报,2024,52(3):872-884,13.基金项目
国家自然科学基金(No.61874157,No.71971151) National Natural Science Foundation of China(No.61874157,No.71971151) （No.61874157,No.71971151）
