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DyPipe: A Holistic Approach to Accelerating Dynamic Neural Networks with Dynamic Pipelining

文献类型：期刊论文

作者Zhuang, Yi-Min1,2; Hu, Xing2; Chen, Xiao-Bing1,2; Zhi, Tian2
刊名JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
出版日期2023-07-01
卷号38期号:4页码:899-910
关键词dynamic neural network (NN) deep neural network (DNN) accelerator dynamic pipelining
ISSN号1000-9000
DOI10.1007/s11390-021-1161-y
英文摘要Dynamic neural network (NN) techniques are increasingly important because they facilitate deep learning techniques with more complex network architectures. However, existing studies, which predominantly optimize the static computational graphs by static scheduling methods, usually focus on optimizing static neural networks in deep neural network (DNN) accelerators. We analyze the execution process of dynamic neural networks and observe that dynamic features introduce challenges for efficient scheduling and pipelining in existing DNN accelerators. We propose DyPipe, a holistic approach to optimizing dynamic neural network inferences in enhanced DNN accelerators. DyPipe achieves significant performance improvements for dynamic neural networks while it introduces negligible overhead for static neural networks. Our evaluation demonstrates that DyPipe achieves 1.7x speedup on dynamic neural networks and maintains more than 96% performance for static neural networks.
资助项目Beijing Natural Science Foundation[JQ18013] ; National Natural Science Foundation of China[61925208] ; National Natural Science Foundation of China[61732007] ; National Natural Science Foundation of China[61732002] ; National Natural Science Foundation of China[61906179] ; Strategic Priority Research Program of Chinese Academy of Sciences (CAS)[XDB32050200] ; Youth Innovation Promotion Association CAS ; Beijing Academy of Artificial Intelligence (BAAI) ; Xplore Prize
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001102032000012
出版者SPRINGER SINGAPORE PTE LTD
源URL[http://119.78.100.204/handle/2XEOYT63/38065]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhi, Tian
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhuang, Yi-Min,Hu, Xing,Chen, Xiao-Bing,et al. DyPipe: A Holistic Approach to Accelerating Dynamic Neural Networks with Dynamic Pipelining[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2023,38(4):899-910.
APA Zhuang, Yi-Min,Hu, Xing,Chen, Xiao-Bing,&Zhi, Tian.(2023).DyPipe: A Holistic Approach to Accelerating Dynamic Neural Networks with Dynamic Pipelining.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,38(4),899-910.
MLA Zhuang, Yi-Min,et al."DyPipe: A Holistic Approach to Accelerating Dynamic Neural Networks with Dynamic Pipelining".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 38.4(2023):899-910.

入库方式： OAI收割

来源：计算技术研究所

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