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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yannan Yang Yaping Liu Zhihong Liu School of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781467386456

The traditional identifier locator split network has many issues such as inflexibility, hard to innovate and difficult to deploy. SDN (Software Defined Network) provides a new direction for designing flexible identifier locator split network. The recent identifier locator split network based on SDN use the OpenFlow switch directly via rewritting the address, which lacks the scalability and utilizes locator address ineffectively. An OpenFlow switch named IDOpenFlow is proposed to support the communication based on identifier. IDOpenFlow switch provides the communication mechanism via encapsulating the packets, which has good scalability and utilizing locator address effectively. IDOpenFlow switch encapsulates and decapsulates packets according flow entries which are installed by SDN controller. Moreover, the prototype system shows that IDOpenFlow effectively supports the communication for both the fixed node and the mobile node. With respect to the issues of software forwarding performance, a high-performance IDOpenFlow switch based on Intel DPDK (which is named A-IDOpenFlow) is proposed. The results of Ixia test tool show that: 1) for packets more than 128 bytes, A-IDOpenFlow switch supports the communication based on identifier at rate of 10Gbit/s; 2) for small packet of 64 bytes, the rate of A-IDOpenFlow is 7.25 times faster than the rate of IDOpenFlow.

关键词： Switches Protocols Software Routing Servers Scalability

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NR-MPI: A non-stop and fault resilient MPI supporting programmer defined data backup and restore for E-scale super computing systems

Supercomputing Frontiers and Innovations

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Supercomputing Frontiers and Innovations 2016年第1期3卷 4-21页

作者： Suo, Guang Lu, Yutong Liao, Xiangke Xie, Min Cao, Hongjia State Key Laboratory of High Performance Computing National University of Defense Technology Changsha Hunan Province China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha Hunan Province China

Fault resilience has became a major issue for HPC systems, particularly, in the perspective of future E-scale systems, which will consist of millions of CPU cores and other components. MPI-level fault tolerant constructs, such as ULFM, are being proposed to support software level fault tolerance. However, there are few systematic evaluations by application programmers using benchmarks or pseudo applications. This paper proposes NR-MPI, a Non-stop and Fault Resilient MPI, supporting programmer defined data backup and restore. To help programmers write fault tolerant programs, NR-MPI provides a set of friendly programming interfaces and a state transition diagram for data backup and restore. This paper focuses on design, implementation and evaluation of NR-MPI. Specifically,this paper puts emphases on failure detection in MPI library, friendly programming interface extending for NR-MPI and examples of fault tolerant programs based NRMPI. Furthermore, to support failure recovery of applications, NR-MPI implements data backup interfaces based on double in-memory checkpoint/*** conduct experiments with both NPB benchmarks and Sweep3D on TH supercomputer in NSCC-TJ. Experimental results show that NR-MPI based fault tolerant programs can recover from failures online without restarting, and the overhead is small even for applications with tens of thousands of cores. © The Authors 2016.

关键词： Message passing

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EmSBoT: A lightweight modular software framework for networked robotic systems

EmSBoT: A lightweight modular software framework for network...

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International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Long Peng Fei Guan Luc Perneel Hasan Fayyad-Kazan Martin Timmerman Department of Electronics and Informatics Vrije Universiteit Brussel (VUB) Brussel-Belgium National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467385244

Developing applications for modern complex networked robotic systems is more challenging due to the introduction of possibly sophisticated communication and coordination aspects. In this paper, we propose EmSBoT, a lightweight embedded component-based software framework targeting resource-constrained networked robotic systems. EmSBoT provides a unified Application Program Interface (API) that hides the heterogeneous distributed environment from applications. Its OS abstraction layer endows it with OS independence and portability. A port-based communication mechanism is adopted to exchange message between loosely coupled components, making the system with fault-tolerance capability. By isolating the communication channels as separate agents, the framework provides uniform and transparent message-passing for agents over node boundaries. We describe the architecture, programming model and core features of EmSBoT in this paper, together with the performance evaluation and behavior validation to demonstrate its efficiency and feasibility.

关键词： Ports (Computers) Robot kinematics Real-time systems Programming Operating systems

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GDSW: A General Framework for distributed Sliding Window over Data Streams

GDSW: A General Framework for Distributed Sliding Window ove...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Huan Chen Yijie Wang Yuan Wang Xingkong Ma Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan P. R. China

ISBN: (纸本)9781509053827

The big data era is characterized by the emergence of live data with high volume and fast arrival rate, it poses a new challenge to stream processing applications: how to process the unbounded live data in real time with high throughput. The sliding window technique is widely used to handle the unbounded live data by storing the most recent history of streams. However, existing centralized solutions cannot satisfy the requirements for high processing capacity and low latency due to the single-node bottleneck. Moreover, existing studies on distributed windows primarily focus on specific operators, while a general framework for processing various window-based operators is wanted. In this paper, we firstly classify the window-based operators to two categories: data-independent operators and data-dependent operators. Then, we propose GDSW, a general framework for distributed count-based sliding window, which can handle both of data-independent and data-dependent operators. Besides, in order to balance system load, we further propose a dynamic load balance algorithm called DAD based on buffer usage. Our framework is implemented on Apache Storm 0.10.0. Extensive evaluation shows that GDSW can achieve sub-second latency, and 10X improvement in throughput compared with centralized processing, when processing rapid data rate or big size window.

关键词： distributed databases Storms parallel processing Semantics Sparks distributed processing Real-time systems

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A C-SVM Based Anomaly Detection Method for Multi-Dimensional Sequence over Data Stream

A C-SVM Based Anomaly Detection Method for Multi-Dimensional...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Han Bao Yijie Wang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan P. R. China

ISBN: (纸本)9781509053827

Anomaly detection over multi-dimensional data stream has attracted considerable attention recently in various fields, such as network, finance and aerospace. In many cases, anomalies are composed of a sequence of multi-dimensional data, and it's necessary to detect this type of anomalies accurately and efficiently over data stream. Existing online methods of anomaly detection merely focus on the single-dimensional sequence. What's more, current studies about multi-dimensional sequence are mainly concentrated on static database. However, the anomaly detection for multi-dimensional sequence over data stream is much more difficult, due to the complexity of multidimensional sequence processing, the dynamic nature of data stream and the unbalance between normal and abnormal data. Facing these challenges, we propose an anomaly detection method for multi-dimensional sequence over data stream based on cost sensitive support vector machine (C-SVM) called ADMS. First, to improve the accuracy and efficiency, the ADMS transforms multi-dimensional sequences into feature vectors in a lossless way and prunes worthless features of these vectors. And then, the ADMS can detect abnormal sequences over dynamically imbalanced data stream by lively testing these vectors based on C-SVM. Experiments show that the false negative rate (FNR) of the ADMS is lower than 5%, the false positive rate (FPR) is lower than 7%, and the throughput is improved 42% by pruning worthless features. In addition, the AMDS performs well when there are concept drifts over the data stream.

关键词： Feature extraction Training Transforms Heuristic algorithms Testing Hidden Markov models Databases

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Benchmarking the Powering Computations for Application Tuning

Benchmarking the Powering Computations for Application Tunin...

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International Conference on Software Analysis, Testing and Evolution (SATE)

作者： Yongang Che Chuanfu Xu Zhenghua Wang Computer College National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) National University of Defense Technology Changsha China

ISBN: (纸本)9781509045181

Powering is an important operation in many computation intensive workloads. This paper investigates the performance of different styles to calculate the powering operations from the application level. A series of small benchmark codes that calculate the powering operations in different ways are designed. Their performance is evaluated on Intel Xeon CPU under Intel compilation environments. The results show that the number of floating-point operations and the related runtime are sensitive to the value of the exponent Y and how it is used. When Y is an immediate integer number whose value is known at compile time, the cost of powering is much less than the situation when Y is an integer variable whose value is known at runtime. When Y is defined as a real variable, the cost of powering is always high, be it equals to an integer number or not. Based on the investigations, performance optimizations are applied to a kernel subroutine from a real-world supersonic combustion simulation code, which intensively involves powering operations. The result shows that the performance of that subroutine is improved for 13.25 times on the Intel Xeon E5-2692 CPU.

关键词： Benchmark testing Arrays Libraries Runtime Signal processing algorithms Hardware

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Area-efficient high-throughput sorted QR decomposition-based MIMO detector on FPGA

Area-efficient high-throughput sorted QR decomposition-based...

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IEEE International Conference on Computer and Communications, ICCC 2015

作者： Zhou, Tong Guo, Song Lei, Yuanwu Dou, Yong National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467381253

This paper aimed to improve MIMO detector's performance in both throughput and cost. Thus, it presents a FPGA architecture implementation for the SQRD detection in a 4 × 4 16-QAM MIMO wireless communication systems. The exploitation of fine-grained parallelism and coarse-grained parallelism strategies are responsible for bettering the performance of the implementation. Besides, this paper proposes a method to ensure the correctness of the implementation of time-sharing modules, which is general and applicable to any MIMO detector implementation. The work results in a real-time FPGA-based implementation delivering 32 MSQRD/s with 5.2 us latency and lowering more than 50\% cost in hardware resources on a Xilinx Virtex6. © 2015 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Optimized deep belief networks on CUDA GPUs

Optimized deep belief networks on CUDA GPUs

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International Joint Conference on Neural Networks, IJCNN 2015

作者： Li, Teng Dou, Yong Jiang, Jingfei Wang, Yueqing Lv, Qi National Laboratory for Parallel and Distributed Processing National University of Defense and Technology Changsha China

ISBN: (纸本)9781479919604

A deep belief network (DBN) is an important branch of deep learning models and has been successfully applied in many machine learning and pattern recognition fields such as computer vision and speech recognition. However, the training of billions of parameters in DBN is computationally challenging for modern central processing units (CPUs). Many studies have reported the efficient implementations of the pre-training process of DBNs for graphics processing units (GPUs), but few studies have mentioned the fine-tuning process of DBNs. In this paper, we describe an efficient DBN implementation on the GPU, including the pre-training and fine-tuning processes. Experimental results show that our proposed method on the GPU (NVIDIA Tesla K40c) achieves up to 22 speedups on the pre-training process and 33 speedups on the fine-tuning processes compared with conventional CPU (Intel Core i7-4790K) implementations. Moreover, the performance of our algorithm is superior to that of the OpenBLAS library on the CPU and the CUBLAS library on the GPU. © 2015 IEEE.

关键词： Graphics processing unit

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Mod (2P-1) Shuffle Memory-Access Instructions for FFTs on Vector SIMD DSPs

Mod (2P-1) Shuffle Memory-Access Instructions for FFTs on Ve...

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IEEE Computer Society Annual Symposium on VLSI

作者： Sheng Liu Hanyan Chen Jianghua Wan Yaohua Wang College of Computer National University of Defense Technology Changsha Hunan China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9781467390408

Binary Exchange Algorithm (BEA) always introduces excessive shuffle operations when mapping FFTs on vector SIMD DSPs. This can greatly restrict the overall performance. We propose a novel mod (2P-1) shuffle function and Mod-BEA algorithm (MBEA), which can halve the shuffle operation count and unify the shuffle mode. Such unified shuffle mode inspires us to propose a set of novel mod (2P-1) shuffle memory-access instructions, which can totally eliminate the shuffle operations. Experimental results show that the combination of MBEA and the proposed instructions can bring 17.2%-31.4% performance improvements at reasonable hardware cost, and compress the code size by about 30%.

关键词： Digital signal processing Hardware Pipelines Computer architecture Linearity Computers Software

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A data-driven mechanism for large-scale data distribution

A data-driven mechanism for large-scale data distribution

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Proceedings of the Biannual World Automation Congress

作者： Peichang Shi Yiying Li Bo Ding Longquan Jiang Hui Liu Jie Zhang National Key Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan CN National Key Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China National University of Defense Technology Changsha Hunan CN China Electr. Equip. & Syst. Eng. Co. Ltd. China

As The integration of Physical space and cyberspace, the large-scale data distributing to diversification terminal which is geographical distribution of mass has become a huge challenge. When the data size can't be processed by the technology for traditional scope, how to deal with the user quality of service and efficient use of system resources has become an important issue of concern, with the resources becoming limited. This paper presents a data-driven mechanism for large-scale data distribution which is consists of four core part of the data production, data collection and pre-processing, data analysis engine, data consumption, aims to excavate the valuable information to improve the efficiency of resource use and accurate fault location for the Large-scale data distribution system. At the same time, this paper studies the resource scheduling optimization with analyzing data driven for the system behavior and Fault location with analyzing data-driven environment, which proves the effectiveness for the operation of the Large-scale data distribution system optimization by the data-driven working.

关键词： Servers Monitoring distributed databases Big data Real-time systems Business

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