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IEEE International Symposium on Object/Component/Service-Oriented Real-Time distributed Computing Workshops (ISORCW)

作者： Dianxi Shi Zhendong Wu Bo Ding Huining Yan National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

Context situation, which means a snapshot of the status of the real world, is formed by integrating a large amount of contexts collected from various resources. How to get the context situation and use the situation to provide better services is a challenging issue. In this paper, we focused on this challenge on the basis of the mobile cloud computing architecture. An abstract model is proposed in this paper to uniformly collect the context and send them to cloud. A rule-based large-scale context aggregation algorithm is also proposed which utilizes the MapReduce computing paradigm. Finally, a large-scale context management framework based on the abstract model and the context aggregation algorithm is proposed, and a real-time traffic demo is implemented to verify the validity of the framework.

关键词： Context Mobile handsets Real time systems Sensors Servers Mobile communication Context modeling

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App-Net: A Hybrid Neural Network for Encrypted Mobile Traffic Classification

App-Net: A Hybrid Neural Network for Encrypted Mobile Traffi...

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IEEE Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Xin Wang Shuhui Chen Jinshu Su College of Computer Science and Technology National University of Defense Technology National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186962

With the exponential growth of mobile traffic data, mobile traffic classification is in a great need. It is an essential step to improve the performance of network services such as QoS and security monitoring. However, the widespread use of encrypted protocols, especially the TLS protocol, has posed great challenges to traditional traffic classification techniques. As the rule-based deep packet inspection approaches are ineffective for encrypted traffic classification, various machine learning methods have been studied and used. Recently, deep learning solutions which enable automatic feature extraction are also proposed to classify encrypted traffic. In this paper we propose App-Net, an end-to-end hybrid neural network, to learn effective features from raw TLS flows for mobile app identification. App-Net is designed by combining RNN and CNN in a parallel way. So that it can learn a joint flow-app embedding to characterize both flow sequence patterns and unique app signatures. We evaluate App-Net on a real-world dataset that covering 80 apps. The results show that our method can achieve an excellent performance and outperform the state-of-the-art methods.

关键词： Cryptography Feature extraction Payloads Recurrent neural networks Machine learning Convolutional neural networks

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Reduced complexity tree-structured conditional random field for all-words word sense disambiguation

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Journal of Computational Information Systems 2012年第3期8卷 1177-1186页

作者： Zhou, Yun Wang, Ting Wang, Zhiyuan Xie, Songxian Computer School National University of Defense Technology Changsha 410073 China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

In this paper, we apply tree-structured conditional random field (TCRF) to all-words word sense disambiguation (WSD), where the graphical structure of TCRF is the dependency syntax tree produced by Minipar. The extremely large label space and high time complexity of TCRF hinders its application in semantic parsing, especially in all-words WSD, and we focus on reducing the time complexity of TCRF in this paper. The running time of TCRF is reduced significantly by edge feature selection and parallelization in training phase and beam search strategy in decoding phase. We evaluate the TCRF method on the English all-words task of Senseval-3, and the F1 value of TCRF method is 0.668, which outperforms the best result 0.652 in Senseval-3. For convenience of comparison, our training set only includes a part of Semcor, which reserves the space for improvement. Furthermore, the practical problem in the fields of information retrieval and natural language processing, often has a large label space and tree-structured information, which can also be solved by the TCRF method proposed in this paper. 1553-9105/Copyright © 2012 Binary Information Press.

关键词： Semantics

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Feature and Performance Comparison of FaaS Platforms 14

Feature and Performance Comparison of FaaS Platforms

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14th IEEE International Conference on Software Engineering and Service Science, ICSESS 2023

作者： Ma, Penghui Shi, Peichang Yi, Guodong College of Computer Science National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China College of Computer Science National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems Changsha410073 China Xiangjiang Lab Changsha410073 China School of Advanced Interdisciplinary Studies Hunan University of Technology and Business Changsha410073 China

ISBN: (纸本)9798350336269

With serverless computing offering more efficient and cost-effective application deployment, the diversity of serverless platforms presents challenges to users, including platform lock-in and costly migration. Moreover, due to the black box nature of function computing, traditional performance benchmarking methods are not applicable, necessitating new studies. This article presents a detailed comparison of six major public cloud function computing platforms and introduces a benchmarking framework for function computing performance. This framework aims to help users make comprehensive comparisons and select the most suitable platform for their specific needs. © 2023 IEEE.

关键词： Benchmarking

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Device View Redundancy: an adaptive low-overhead fault tolerance mechanism for many-core system

Device View Redundancy: an adaptive low-overhead fault toler...

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International Workshop on Intelligent Communication and Social Networks

作者： Wentao Jia Chunyuan Zhang Jian Fu National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology Institute for Informatics University of Amsterdam

ISBN: (纸本)9781479909735

Continued increasing of fault rate in integrate circuit makes processors more susceptible to errors, especially many-core processor. Meanwhile, most systems or applications do not need full fault coverage, which has excessive overhead. So on-demand fault tolerance is desired for these applications. In this paper, we propose an adaptive low-overhead fault tolerance mechanism for many-core system, called Device View Redundancy (DVR). It treats fault tolerance as a device that can be configured and used by application when high reliability is needed. Nevertheless, DVR exploits the idle resources for low-overhead fault tolerance, which is based on the observation that the utilization of many-core system is low due to lack of parallelism in application. Finally, the experiment shows that the performance overhead of DVR is reduced by 16% to 98% compared with full Dual Modular Redundancy (DMR).

关键词： On-demand redundancy Idle resource exploitation Dynamic coupling Low-overhead Many core system

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IWFR: Exploiting full-duplex in wireless relay networks

IWFR: Exploiting full-duplex in wireless relay networks

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International Conference on Information Science and technology (ICIST)

作者： Yong Lu Shaohe Lv Xiaodong Wang Xingming Zhou National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan China

Traditional wireless relay networks have large end-to-end time delay and low throughput because of the limit that it can't receive and forward at the same time. In this paper, we proposed IWFR: Immediate Wireless Full-Duplex Relay which exploits the advantages of full-duplex to shorten the end-to-end time delay and improve the throughput. At the same time, we designed a new implicit acknowledgement mechanism, which can eliminate the ACK overheads and evidently improve the throughput of the relay. To implement IWFR, we also modified the full-duplex node architecture to make it support for immediate relay. Simulation shows that IWFR shortens the end-to-end time delay by 60% on average and improves the throughput to 240% of the original relay.

关键词： Wireless communication Throughput Delay effects Wireless sensor networks Interference Relay networks (telecommunications)

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EmbRace: Accelerating Sparse Communication for distributed Training of NLP Neural Networks

arXiv

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arXiv 2021年

作者： Li, Shengwei Lai, Zhiquan Li, Dongsheng Zhang, Yiming Ye, Xiangyu Duan, Yabo National Key Laboratory of Parallel Distributed Processing Computer College National University of Defense Technology China Xiamen University China

distributed data-parallel training has been widely adopted for deep neural network (DNN) models. Although current deep learning (DL) frameworks scale well for dense models like image classification models, we find that these DL frameworks have relatively low scalability for sparse models like natural language processing (NLP) models that have highly sparse embedding tables. Most existing works overlook the sparsity of model parameters thus suffering from significant but unnecessary communication overhead. In this paper, we propose EmbRace, an efficient communication framework to accelerate communications of distributed training for sparse models. EmbRace introduces Sparsity-aware Hybrid Communication, which integrates AlltoAll and model parallelism into data-parallel training, so as to reduce the communication overhead of highly sparse parameters. To effectively overlap sparse communication with both backward and forward computation, EmbRace further designs a 2D Communication Scheduling approach which optimizes the model computation procedure, relaxes the dependency of embeddings, and schedules the sparse communications of each embedding row with a priority queue. We have implemented a prototype of EmbRace based on PyTorch and Horovod, and conducted comprehensive evaluations with four representative NLP models. Experimental results show that EmbRace achieves up to 2.41X speedup compared to the state-of-the-art distributed training baselines. Copyright © 2021, The Authors. All rights reserved.

关键词： Embeddings

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DLSM: Decoupled Live Storage Migration with distributed Device Mapper Storage

DLSM: Decoupled Live Storage Migration with Distributed Devi...

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2014 IEEE 8th International Symposium on Service Oriented System Engineering

作者： Zhaoning Zhang Ziyang Li Kui Wu Huiba Li Yuxing Peng Xicheng Lu National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China University of Victoria Victoria BC CA

As a key technique in cloud computing, live virtual machine (VM) migration makes cloud computing elastic and renders more efficient resource scheduling. In many cases, live storage migration is also desirable. Compared to live VM migration, however, live storage migration is relatively slow. The speed gap between live VM migration and live storage migration may lead to poor Quality of Service (QoS) for cloud users. In this paper, we present a new resource migration scheme, called Decoupled Live Storage Migration (DLSM), which decouples the live storage migration from the live VM migration. DLSM can migrate the VM immediately, while data blocks actually required by the VM are moved on demand at later times. It achieves the on-demand data migration at the storage level without the need of modifying the hypervisor. The key contribution of DLSM is that it reduces the network traffic and speeds up the live storage migration, by completely eliminating iterative copy of dirty data over the network. This good property is achieved without relying on any tracking mechanism for dirty data blocks. Experimental evaluation demonstrates the efficiency and effectiveness of DLSM.

关键词： Data transfer Switches Virtual machine monitors Convergence Linux Kernel Bandwidth

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Grid computing in China

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Journal of Grid Computing 2004年第2期2卷 193-206页

作者： Yang, Guangwen Jin, Hai Li, Minglu Xiao, Nong Li, Wei Wu, Zhaohui Wu, Yongwei Tang, Feilong Department of Computer Science and Technology Tsinghua University Beijing China School of Computer Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China College of Computer Science Zhejiang University Hangzhou 310027 China

Grid computing presents a new trend to distributed computation and Internet applications, which can construct a virtual single image of heterogeneous resources, provide uniform application interface and integrate widespread computational resources into super, ubiquitous and transparent aggregation. In the adoption of Grid computing, China, who is facing more resource heterogeneity and other specific demands, has put much effort on both research and practical utilization. In this paper, we introduce the major China Grid research projects and their perspective applications. First we give the overview of the four government-sponsored programs in Grid, namely the China national Grid, ChinaGrid, NSFC Grid, and ShanghaiGrid. Then we present six representative ongoing Grid systems in details, which are categorized into Grid middleware and Grid application. This paper provides the general picture of Grid computing in China, and shows the great efforts, devotion and confidence in China to use Grid technology to boost the society, economics and scientific research. © Springer 2004.

关键词： Grid computing

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Optimization techniques of on-chip memory system based on UltraSPARC architecture

Optimization techniques of on-chip memory system based on Ul...

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Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)

作者： Anwen Huang Jun Gao Chaochao Feng Minxuan Zhang Key Laboratory of Science and Technology of National Defense of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

It is of great significance to optimize the design of on-chip memory system for improving the performance of multi-core processor. This paper describes the organization of on-chip memory hierarchy in UltraSPARC T2, analyzes the procedure of dealing with the memory access request from multi-core processor in detail. To get the basic parameters of timing characteristic and area consumption, the primary element of on-chip memory system is simulated by ModelSim and synthesized by Synopsys Design Complier with 90 nm standard cell library. Aimed at the potential limiting factor of improving the performance of memory hierarchy, corresponding optimization techniques of critical elements in memory system are explored finally.

关键词： System-on-a-chip Elliptic curve cryptography Hardware Costs Algorithm design and analysis Random access memory Clocks Registers Elliptic curves Protection

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