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Unified virtual memory support for deep CNN accelerator on soC FPGA 1

15th International Conference on Algorithms and Architectures for parallel Processing, ICA3PP 2015

作者： Xiao, Tao Qiao, Yuran Shen, Junzhong Yang, Qianming Wen, Mei College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

Cooperation of CPU and hardware accelerator on SoC FPGA to accomplish computational intensive tasks, provides significant advantages in performance and energy efficiency. However, current operating systems provide little support for accelerators: the OS is unaware that a computational task can be executed either on a CPU core or an accelerator, and provides no assistance in efficient management of data sharing between CPU and accelerator on the DRAM, such as zero copy, data coherence. It’s also hard for current OS to allocate large contiguous physical memory space for accelerator. In this paper, we select the Xilinx ZYNQ as target and qualitatively analyze methods of sharing data. Besides using high-performance (HP) AXI interfaces of the ZYQN device, we develop a novel memory management system for FPGA-based accelerator. It provides a unified virtual space for CPU cores and accelerator so that they can access the same memory space in the operating systems user space. For a deep convolutional neural network task, our design gains up to speed-up of 5. 34x compared to traditional processoraccelerator cooperation. © Springer International Publishing Switzerland 2015.

关键词： Energy efficiency

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Tinman: Eliminating confidential mobile data exposure with security oriented offloading 15

Tinman: Eliminating confidential mobile data exposure with s...

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10th European Conference on Computer Systems, EuroSys 2015

作者： Xia, Yubin Liu, Yutao Tan, Cheng Ma, Mingyang Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems China Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450332385

The wide adoption of smart devices has stimulated a fast shift of security-critical data from desktop to mobile devices. However, recurrent device theft and loss expose mobile devices to various security threats and even physical attacks. This paper presents TinMan, a system that protects confidential data such as web site password and credit card number (we use the term cor to represent these data, which is short for Confidential Record) from being leaked or abused even under device theft. TinMan separates accesses of cor from the rest of the functionalities of an app, by introducing a trusted node to store cor and offloading any code from a mobile device to the trusted node to access cor. This completely eliminates the exposure of cor on the mobile devices. The key challenges to TinMan include deciding when and how to efficiently and transparently offload execution;Tin-Man addresses these challenges with security-oriented offloading with a low-overhead tainting scheme called asymmetric tainting to track accesses to cor to trigger offloading, as well as transparent SSL session injection and TCP payload replacement to offload accesses to cor. We have implemented a prototype of TinMan based on Android and demonstrated how TinMan protects the information of user's bank account and credit card number without modifying the apps. Evaluation results also show that TinMan incurs only a small amount of performance and power overhead. Copyright © 2015 ACM.

关键词： Crime

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Ranking Open Source Software Based on Crowd Wisdom

Ranking Open Source Software Based on Crowd Wisdom

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2015 6th IEEE International Conference on Software Engineering and Service Science(ICSESS 2015)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing School of Computer National University of Defense Technology

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in Stack Overflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in Stack Overflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Software ranking Open Source Crowd Wisdom Open Source Community

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Looking for Information Source from Online Social Network with Incomplete Observation

Looking for Information Source from Online Social Network wi...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Peng Shi Lianhong Ding Tianle Zhang National Center for Materials Service Safety University of Science and Technology Beijing Beijing China School of Information Beijing Wuzi University Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781509035595

Online social network has become an important media for information spreading. To target the origin of rumors and well understand the cause of event, information source in social network should be found out. Unfortunately, because of the huge and complex structure of social network, it is nearly impossible to monitor the complete online social network. To solve this problem, the paper gives a method to look for information source with incomplete observation. The basis of the method is the correlation between activated time and network topology structure. Some experiments are executed and the effect of different sampling methods was analyzed as well. Experiments on BA, WS and Facebook show that the method can produce satisfied results with incomplete observation.

关键词： Observers Network topology Diffusion processes Facebook distributed computing

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Ranking open source software based on crowd wisdom

Ranking open source software based on crowd wisdom

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing National University of Defense Technology ChangSha Hunan China

ISBN: (纸本)9781479983544

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in StackOverflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in StackOverflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Open source software Data models Joining processes Software reusability Internet

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OSSEAN: Mining Crowd Wisdom in Open Source Communities

OSSEAN: Mining Crowd Wisdom in Open Source Communities

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2015 IEEE Symposium on Service-Oriented System Engineering

作者： Gang Yin Tao Wang Huaimin Wang Qiang Fan Yang Zhang Yue Yu Cheng Yang National Laboratory of Parallel and Distributed Computing National University of Defense Technology ChangSha Hunan China

Nowadays open source software represents a successful crowd-based software production model and is becoming an ecosystem combining huge amounts of software producers (such as software developers) and consumers (such as software users and customers). Lots of research work has been conducted on analyzing software artifacts created by producers, but few of them reveal the power of feedback from consumers which we believe is very important for the evaluation and evolution of open source software. This paper introduces OSSEAN, a platform for Open Source Software Evaluating, Analyzing and Networking. OSSEAN divides the open source communities into two groups: software production communities and software consumption communities. The former contain structured software artifacts such as projects, source code and issues, while the latter are full of textual documents with rich semantics of user feedback. We show the power of OSSEAN with some interesting demos by analyzing more than 200 thousands of open source projects and 10 million documents.

关键词： Communities Production Data mining Crawlers Open source software Ecosystems

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Cooperative monitoring BGP among autonomous systems

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Security and Communication Networks 2015年第10期8卷 1943-1957页

作者： Hu, Ning Wang, BaoSheng Liu, Xin National Key Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha Hunan China

As the de facto Internet inter-domain routing protocol, BGP protocol has a number of vulnerabilities and weakness. Monitoring BGP is an effective way to improve the security of inter-domain routing. This paper presents a cooperative BGP monitoring method, which is called cooperative information sharing model (CoISM). CoISM is based on self-organization and can be used to solve some problems during BGP monitoring, such as route validation and bogus route notification delivery. CoISM provides autonomous systems with a more comprehensive information view by introducing information diffuse reflection based on initiative inquiry and making use of the relativity of monitoring information. CoISM optimizes the information transmission by leveraging the data locality caused by BGP policy and implements ISP coordination with low communication and deployment cost. More specifically, CoISM provides a self-organizing and incentive mechanism, which drives autonomous systems to coordinate independently and shares information on-demand. CoISM supports incremental deployment and can also be applied to a wide range of inter-domain cooperative management applications such as inter-domain routing failure analysis and intrusion detection. © 2014 John Wiley & Sons, Ltd.

关键词： Monitoring

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MatrixMap: Programming Abstraction and Implementation of Matrix Computation for Big Data Applications

MatrixMap: Programming Abstraction and Implementation of Mat...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yaguang Huangfu Jiannong Cao Hongliang Lu Guanqing Liang Department of Computing The Hong Kong Polytechnic University Parallel and Distributed Processing Laboratory National University of Defense Technology

The computation core of many big data applications can be expressed as general matrix computations, including linear algebra operations and irregular matrix operations. However, existing parallel programming systems such as Spark do not have programming abstraction and efficient implementation for general matrix computations. In this paper, we present MatrixMap, a unified and efficient data-parallel system for general matrix computations. MatrixMap provides powerful yet simple abstraction, consisting of a distributed data structure called bulk key matrix and a computation interface defined by matrix patterns. Users can easily load data into bulk key matrices and program algorithms into parallel matrix patterns. MatrixMap outperforms current state-of-the-art systems by employing three key techniques: matrix patterns with lambda functions for irregular and linear algebra matrix operations, asynchronous computation pipeline with optimized data shuffling strategies for specific matrix patterns and in-memory data structure reusing data in iterations. Moreover, it can automatically handle the parallelization and distribute execution of programs on a large cluster. The experiment results show that MatrixMap is 12 times faster than Spark.

关键词： Data structures Programming Linear algebra Machine learning algorithms Sparks Sparse matrices Computational modeling

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MABP: an optimal resource allocation approach in data center networks

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Science China(Information Sciences) 2014年第10期57卷 230-245页

作者： LI XiaoLing WANG HuaiMin DING Bo LI XiaoYong National Key Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology

In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.

关键词： data center network resource allocation workload substrate network optimality distributed constraint optimization

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Feverfew: a scalable coverage-based hybrid overlay for Internet-scale pub/sub networks

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Science China(Information Sciences) 2014年第5期57卷 51-64页

作者： MA XingKong WANG YiJie SUN WeiDong National Key Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology

The publish/subscribe(pub/sub)paradigm is a popular communication model for data dissemination in large-scale distributed ***,scalability comes with a contradiction between the delivery latency and the memory *** one hand,constructing a separate overly per topic guarantees real-time dissemination,while the number of node degrees rapidly increases with the number of *** the other hand,maintaining a bounded number of connections per node guarantees small memory cost,while each message has to traverse a large number of uninterested nodes before reaching the *** this paper,we propose Feverfew,a coverage-based hybrid overlay that disseminates messages to all subscribers without uninterested nodes involved in,and increases the average number of node connections slowly with an increase in the number of subscribers and *** major novelty of Feverfew lies in its heuristic coverage mechanism implemented by combining a gossip-based sampling protocol with a probabilistic searching *** on the practical workload,our experimental results show that Feverfew significantly outperforms existing coverage-based overlay and DHT-based overlay in various dynamic network environments.

关键词： publish/subscribe coverage-based data dissemination topic-based gossip

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