FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators

doi:10.1007/s11390-021-1406-9

	FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators
	Liu, Lei 1,2; Ma, Xiu 1,2; Liu, Hua-Xiao 1,2; Li, Guang-Li 3,4; Liu, Lei 3
	2022-10-01
发表期刊	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
ISSN	1000-9000
卷号	37 期号:5 页码:1200-1220
摘要	There are a wide variety of intelligence accelerators with promising performance and energy efficiency, deployed in a broad range of applications such as computer vision and speech recognition. However, programming productivity hinders the deployment of deep learning accelerators. The low-level library invoked in the high-level deep learning framework which supports the end-to-end execution with a given model, is designed to reduce the programming burden on the intelligence accelerators. Unfortunately, it is inflexible for developers to build a network model for every deep learning application, which probably brings unnecessary repetitive implementation. In this paper, a flexible and efficient programming framework for deep learning accelerators, FlexPDA, is proposed, which provides more optimization opportunities than the low-level library and realizes quick transplantation of applications to intelligence accelerators for fast upgrades. We evaluate FlexPDA by using 10 representative operators selected from deep learning algorithms and an end-to-end network. The experimental results validate the effectiveness of FlexPDA, which achieves an end-to-end performance improvement of 1.620x over the low-level library.
关键词	deep learning accelerator programming framework domain-specific language
DOI	10.1007/s11390-021-1406-9
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2017YFB1003103] ; Natural Science Research Foundation of Jilin Province of China[20190201193JC] ; Fundamental Research Funds for the Central Universities
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS记录号	WOS:000870734200013
出版者	SCIENCE PRESS
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/19773
专题	中国科学院计算技术研究所期刊论文
通讯作者	Liu, Hua-Xiao
作者单位	1.Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China 2.Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Liu, Lei,Ma, Xiu,Liu, Hua-Xiao,et al. FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2022,37(5):1200-1220.
APA	Liu, Lei,Ma, Xiu,Liu, Hua-Xiao,Li, Guang-Li,&Liu, Lei.(2022).FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,37(5),1200-1220.
MLA	Liu, Lei,et al."FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 37.5(2022):1200-1220.