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DNNTune: Automatic Benchmarking DNN Models for Mobile-cloud Computing

文献类型：期刊论文

作者Xia, Chunwei1,2; Zhao, Jiacheng1,2; Cui, Huimin1,2; Feng, Xiaobing1,2; Xue, Jingling3
刊名ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION
出版日期2019-12-01
卷号16期号:4页码:26
关键词DNN mobile-cloud computing heterogeneous computing
ISSN号1544-3566
DOI10.1145/3368305
英文摘要Deep Neural Networks (DNNs) are now increasingly adopted in a variety of Artificial Intelligence (AI) applications. Meantime, more and more DNNs are moving from cloud to the mobile devices, as emerging AI chips are integrated into mobiles. Therefore, the DNN models can be deployed in the cloud, on the mobile devices, or even mobile-cloud coordinate processing, making it a big challenge to select an optimal deployment strategy under specific objectives. This article proposes a DNN tuning framework, i.e., DNNTune, that can provide layer-wise behavior analysis across a number of platforms. Using DNNTune, this article further selects 13 representative DNN models, including CNN, LSTM, and MLP, and three mobile devices ranging from low-end to high-end, and two AI accelerator chips to characterize the DNN models on these devices to further assist users finding opportunities for mobile-cloud coordinate computing. Our experimental results demonstrate that DNNTune can find a coordinated deployment achieving up to 1.66x speedup and 15% energy saving comparing with mobile-only and cloud-only deployment.
资助项目National Key R&D Program of China[2016YFB1000402] ; National Natural Science Foundation of China[61802368] ; National Natural Science Foundation of China[61521092] ; National Natural Science Foundation of China[61432016] ; National Natural Science Foundation of China[61432018] ; National Natural Science Foundation of China[61332009] ; National Natural Science Foundation of China[61702485] ; National Natural Science Foundation of China[61872043] ; CCF-Tencent Open Research Fund ; Australian Research Council[RG171010]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000504657400016
出版者ASSOC COMPUTING MACHINERY
源URL[http://119.78.100.204/handle/2XEOYT63/14980]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhao, Jiacheng
作者单位1.Univ Chinese Acad Sci, Sch Comp Sci & Technol, 19 A Yuquan Rd, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, 6 Kexueyuan South Rd Zhongguancun, Beijing 100190, Peoples R China
3.Univ New South Wales, Sch Comp Sci & Engn, Gate 14 Barker St, Sydney, NSW 2052, Australia
推荐引用方式
GB/T 7714		 Xia, Chunwei,Zhao, Jiacheng,Cui, Huimin,et al. DNNTune: Automatic Benchmarking DNN Models for Mobile-cloud Computing[J]. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION,2019,16(4):26.
APA Xia, Chunwei,Zhao, Jiacheng,Cui, Huimin,Feng, Xiaobing,&Xue, Jingling.(2019).DNNTune: Automatic Benchmarking DNN Models for Mobile-cloud Computing.ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION,16(4),26.
MLA Xia, Chunwei,et al."DNNTune: Automatic Benchmarking DNN Models for Mobile-cloud Computing".ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 16.4(2019):26.

入库方式： OAI收割

来源：计算技术研究所

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