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EdgeNN: Efficient Neural Network Inference for CPU-GPU Integrated Edge Devices

EdgeNN: Efficient Neural Network Inference for CPU-GPU Integ...

引用

International Conference on data engineering

作者： Chenyang Zhang Feng Zhang Kuangyu Chen Mingjun Chen Bingsheng He Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering (MOE) and School of Information Renmin University of China School of Computing National University of Singapore

With the development of the architectures and the growth of AIoT application requirements, data processing on edge has become popular. Neural network inference is widely employed for data analytics on edge devices. This paper extensively explores neural network inference on integrated edge devices and proposes EdgeNN, the first neural network inference solution on CPU-GPU integrated edge devices. EdgeNN has three novel characteristics. First, EdgeNN can adaptively utilize the unified physical memory and conduct the zero-copy optimization. Second, EdgeNN involves a novel inference-targeted inter- and intra-kernel CPU-GPU hybrid execution approach, which co-runs the CPU with the GPU to fully utilize the edge device’s computing resources. Third, EdgeNN adopts a fine-grained adaptive inference tuning approach, which can divide the complicated inference structure into sub-tasks mapped to the CPU and the GPU. Experiments show that on six popular neural network inference tasks, EdgeNN brings an average of 3.97×, 3.12×, and 8.80× speedups to inference on the CPU of the integrated device, inference on a mobile phone CPU, and inference on an edge CPU device. Additionally, it achieves 22.02% time benefits to the direct execution of the original programs. Specifically, 9.93% comes from better utilization of unified memory, and 10.76% comes from CPU-GPU hybrid execution. Besides, EdgeNN can deliver 29.14× and 5.70× higher energy efficiency than the edge CPU and the discrete GPU, respectively. We have made EdgeNN available at https://***/ChenyangZhang-cs/EdgeNN.

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Energy-efficient Robust data-centric Storage in Wireless Sensor Networks

Energy-efficient Robust Data-centric Storage in Wireless Sen...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Yongxuan Lai Yufeng Wang Hong Chen School of Information Renmin University of China Beijing P.R.China Key Laboratory of Data Engineering and Knowledge Engineering MOE

In this paper, we propose a new Dynamic datacentric Storage (DDS) mechanism in wireless sensor network. DDS, which is aware of the data distributions of the network, dynamically adjusts the mappings from sensor readings to the storage points to reduce the cost of storing these readings, as well as to balance the storage and workload in the network. Moreover, it takes advantage of the GPSR routing protocol to store multiple copies of readings to improve the robustness of the network with little overhead. Simulation results show that the approach is more energy-efficient and robust than other data-centric schemes.

关键词： energy-efficient robust storage data-centric storage wireless sensor networks

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Towards Video Management over Relational database

Towards Video Management over Relational Database

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International Asia-Pacific Web Conference (APWEB)

作者： Hui Li Xiao Zhang Shan Wang Xiaoyong Du School of Information Key Laboratory of Data Engineering and Knowledge Engineering Shanghai Key Laboratory of Intelligent Information Processing MOE Renmin University of China China

Video has become popular in our daily life for both professional and consumer applications. Both low level video processing and high level semantic video analysis are critically computational tasks in application domains. Most of current video computing tools are developed for specific analytic tasks, they are lack higher level interoperability with database and treat database merely as a relational data storage engine rather than an analytic platform, which causes inefficient data access and massive amount of data movement. In this paper, we study how to support video data management over relational database, and present our initial solutions of video data storage mechanism, video data access method and efficient video analytics. We also illustrate our ongoing prototype system HybVideo that developed in a novel architecture. It integrates above solutions to tackle the major challenges of providing a platform for both storage and analysis of video data.

关键词： Relational databases Memory Videoconference laboratories Engines data analysis Performance analysis Video surveillance Conference management knowledge management

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DSOSW: A Deleting Strategy in Mining Frequent Itemsets over Sliding Window of Stream

DSOSW: A Deleting Strategy in Mining Frequent Itemsets over ...

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International Symposiums on Information Processing (ISIP)

作者： Haifeng Li Hong Chen Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China Renmin University of China Beijing CN

Most traditional mining approaches of frequent item sets consider mainly on databases and thus can use the second storage and need multiple scans which are not adapted to mining of stream. Some new algorithms over stream's sliding window are presented recently, which perform addition and deletion over stream independently, so the common deleting strategy which removes the earliest transaction is used when the window slides. This paper considers both operations together to reduce the computation cost, consequently, three deleting strategies are proposed to improve the performance with little precision loss. The experimental results show that these strategies over current method are effective and efficient.

关键词： data mining Itemsets Writing laboratories data engineering knowledge engineering Transaction databases Information processing Computational efficiency Performance loss

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Web Technologies Research and Development - APWeb 2005 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Yanchun Zhang Katsumi Tanaka Jeffrey Xu Yu Shan Wang Minglu Li

ISBN: (数字)9783540318491

ISBN: (纸本)9783540252078

This volume contains papers selected for presentation at the 7th Asia Pacific Conference on Web Technology (APWeb 2005), which was held in Shanghai, China during March 29–April 1, 2005. APWeb is an international conference series on WWW technologies and is the primary forum for researchers and practitioners from both academia and industry to exchange knowledge on WWW-related technologies and new advanced applications. APWeb 2005 received 420 submissions from 21 countries and regions worldwide, including China, Korea, Australia, Japan, Taiwan, France, UK, Canada, USA, India, Hong Kong, Brazil, Germany, Thailand, Singapore, Turkey, Spain, Greece, Belgium, New Zealand, and UAE. After a thorough review process for each submission by the Program Committee members and expert reviewers recommended by PC members, APWeb 2005 accepted 71 regular research papers (acceptance ratio 16.9%) and 22 short papers (acceptance ratio 5.2%). This volume also includes 6 keynote papers and 11 invited demo papers. The keynote lectures were given by six leading experts: Prof. Ah Chung Tsoi (Australia Research Council), Prof. Zhiyong Liu (National Nature Science Foundation of China), Prof. John Mylopoulos (University of Toronto), Prof. Ramamohanarao (Rao) Kotagiri (University of Melbourne), Prof. Calton Pu (Georgia Tech), and Prof. Zhiwei Xu (Chinese Academy of Sciences).

关键词： Information Storage and Retrieval Information Systems Applications (incl. Internet) Multimedia Information Systems User Interfaces and Human Computer Interaction Computer Communication Networks Computers and Society

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Link prediction in author collaboration network based on BP neural network 3

Link prediction in author collaboration network based on BP ...

引用

3rd International Conference on Mechanical, Electronic and Information Technology engineering, ICMITE 2017

作者： Chen, Chaoqun Deng, Sanhong Lu, Jing School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Lab of Data Engineering and Knowledge Service Nanjing210023 China Jiangsu Institute of Geological Survey Nanjing210018 China

Recently, more and more authors have been encouraged for collaboration because it often produces good results. However, the author collaboration network contains experts in various research directions within various fields, and it is difficult for individual authors to decide which authors are best suited to their expertise. This paper uses the relationships among authors to predict new relationships that may arise, recommending each author with the collaborators they may be interested in. The data source comes from 4-year data in DBLP from 2001 to 2004. After data cleaning, the training set and test set are constructed and then used BP neural network to build model. At the same time, this article compares the performance with Logistic Regression, SVM and Random Forest. The experiment shows that the BP neural network can get better result, and it is feasible to predict links in the author collaboration network. © The Authors, published by EDP Sciences, 2017.

关键词： Forecasting

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Incremental computation for MEDIAN cubes in what-if analysis

Incremental computation for MEDIAN cubes in what-if analysis

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Joint International Conference on Advances in data and Web Management, APWeb/WAIM 2009

作者： Xiao, Yanqin Zhang, Yansong Wang, Shan Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Computer Center Hebei University Baoding Hebei 071002 China Department of Computer Science Harbin Finance College Harbin 150030 China

ISBN: (纸本)9783642006715

What-if analysis is an important type of DSS analysis processing procedure. It analyzes hypothetical scenarios based on historical data. The data cube view must be updated when the what-if condition is changed. Since source data must be kept in order to compute the new aggregate value when new tuples are inserted or deleted, in what-if analysis, incrementally computing a data cube for holistic aggregation functions is a difficult problem. In this paper, we adopt delta cube strategy and work area technique to incrementally compute data cube for MEDIAN function. The size of work area has important influence on the efficiency of the incremental computing. This paper optimizes the size of work area based on the number and the cardinality of dimension attributes of the cuboid. Performance study shows that our algorithms are effective over large databases. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Geometry

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Investigating different syntactic context types and context representations for learning word embeddings

Investigating different syntactic context types and context ...

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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Li, Bofang Liu, Tao Zhao, Zhe Tang, Buzhou Drozd, Aleksandr Rogers, Anna Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shenzhen Graduate School Harbin Institute of Technology China Global Scientific Information and Computing Center Tokyo Institute of Technology China Department of Computer Science University of Massachusetts Lowell United States

ISBN: (纸本)9781945626838

The number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open question what is the best definition of context. We provide a systematical investigation of 4 different syntactic context types and context representations for learning word embeddings. Comprehensive experiments are conducted to evaluate their effectiveness on 6 extrinsic and intrinsic tasks. We hope that this paper, along with the published code, would be helpful for choosing the best context type and representation for a given task. © 2017 Association for Computational Linguistics.

关键词： Embeddings

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A New Dynamic Hash Index for Flash-Based Storage

A New Dynamic Hash Index for Flash-Based Storage

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International Conference on Web-Age Information Management Workshops (WAIM)

作者： Xiang Li Zhou Da Xiaofeng Meng Renmin University of China Beijing CN Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China China

Compared with traditional magnetic disks, flash memory has many advantages and has been used as external storage media for a wide spectrum of electronic devices (such as PDA, MP3, digital camera and mobile phone). As the capacity increases and price drops, it looks like a perfect alternative for magnetic disks. However, due to hardware limitations of flash memory, techniques including storage subsystem and indexing originally designed for magnetic disks can not run smoothly in a flash memory without any modification. In this paper we explore problems of indexing flash-resided data and present a new dynamical hash index for flash memory in two schemas. The analysis and experimental results validate the efficiency of our design.

关键词： Indexes Flash memory Algorithm design and analysis Writing Tuning Indexing Arrays

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Lawyer information integration and recommendation by multi-source information validation

Lawyer information integration and recommendation by multi-s...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Tao Liu Biao Fan He Hu Xiao-Yong Du Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China China School of Information Renmin University of China Beijing China

On the internet, all-round lawyer information is located at separated information sources, which prevent web users from effective information acquisition. In order to build a unified view of separated, heterogeneous, and often redundant lawyer information, we propose a new information integration method using multi-source information cross-validation. Based on the unified integrated data, a lawyer recommendation system is built. Several key technologies are presented and evaluated, including the multi-source information acquisition and validation. Experimental results indicate the key techniques used in the system are effective for lawyer information integration and recommendation.

关键词： Organizations Crawlers Search engines data mining Web pages databases Reliability

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