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Scalability of 3D deterministic particle transport on the Intel MIC architecture

Nuclear Science and Techniques 2015年第5期26卷 88-97页

作者：王庆林刘杰龚春叶邢座程 Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Science and Technology on Space Physics Laboratory

The key to large-scale parallel solutions of deterministic particle transport problem is single-node computation performance. Hence, single-node computation is often parallelized on multi-core or many-core computer architectures. However, the number of on-chip cores grows quickly with the scale-down of feature size in semiconductor technology. In this paper, we present a scalability investigation of one energy group time-independent deterministic discrete ordinates neutron transport in 3D Cartesian geometry(Sweep3D) on Intel's Many Integrated Core(MIC) architecture, which can provide up to 62 cores with four hardware threads per core now and will own up to 72 in the future. The parallel programming model, Open MP, and vector intrinsic functions are used to exploit thread parallelism and vector parallelism for the discrete ordinates method, respectively. The results on a 57-core MIC coprocessor show that the implementation of Sweep3 D on MIC has good scalability in performance. In addition, the application of the Roofline model to assess the implementation and performance comparison between MIC and Tesla K20 C Graphics processing Unit(GPU) are also reported.

关键词：计算机体系结构可扩展性粒子输运三维几何英特尔麦克风离散坐标法计算性能

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Service fault tolerance for highly reliable service-oriented systems: an overview

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Science China(Information Sciences) 2015年第5期58卷 7-18页

作者： ZHENG ZiBin LYU Michael Rung Tsong WANG HuaiMin Shenzhen Research Institute The Chinese University of Hong Kong National Laboratory for Parallel & Distributed Processing National University of Defense Technology

Service-oriented systems are widely-employed in e-business, e-government, finance, management systems, and so on. Service fault tolerance is one of the most important techniques for building highly reliable service-oriented systems. In this paper, we provide an overview of various service fault tolerance techniques,including sections on fault tolerance strategy design, fault tolerance strategy selection, and Byzantine fault tolerance. In the first section, we introduce the design of static and dynamic fault tolerance strategies, as well as the major problems when designing fault tolerance strategies. After that, based on various fault tolerance strategies, in the second section, we identify significant components from a complex service-oriented system, and investigate algorithms for optimal fault tolerance strategy selection. Finally, in the third section, we discuss a special type of service fault tolerance techniques, i.e., the Byzantine fault tolerance.

关键词： fault tolerance software reliability Web service SOA

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Performance of the fixed-point autoencoder

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Tehnicki Vjesnik 2016年第1期23卷 77-82页

作者： Jiang, Jingfei Hu, Rongdong Wang, Dongsheng Xu, Jinwei Dou, Yong Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology 109 DeYa Road ChangShaHunan410073 China

The model of autoencoder is one of the most typical deep learning models that have been mainly used in unsupervised feature learning for many applications like recognition, identification and mining. Autoencoder algorithms are compute-intensive tasks. Building large scale autoencoder model can satisfy the analysis requirement of huge volume data. But the training time sometimes becomes unbearable, which naturally leads to investigate some hardware acceleration platforms like FPGA. The software versions of autoencoder often use single-precision or double-precision expressions. But the floating point units are very expensive to implement on FPGA. Fixed-point arithmetic is often used when implementing autoencoder on hardware. But the accuracy loss is often ignored and its implications for accuracy have not been studied in previous works. There are only some works focused on accelerators using some fixed bit-widths on other neural networks models. Our work gives a comprehensive evaluation to demonstrate the fix-point precision implications on the autoencoder, achieving best performance and area efficiency. The method of data format conversion, the matrix blocking methods and the complex functions approximation are the main factors considered according to the situation of hardware implementation. The simulation method of the data conversion, the matrix blocking with different parallelism and a simple PLA approximation method were evaluated in this paper. The results showed that the fixed-point bit-width did have effect on the performance of autoencoder. Multiple factors may have crossed effect. Each factor would have two-sided impacts for discarding the "abundant" information and the "useful" information at the same time. The representation domain must be carefully selected according to the computation parallelism. The result also showed that using fixed-point arithmetic can guarantee the precision of the autoencoder algorithm and get acceptable convergence speed. © 2016

关键词： Field programmable gate arrays (FPGA)

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Auxo: an architecture-centric framework supporting the online tuning of software adaptivity

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Science China(Information Sciences) 2015年第9期58卷 31-45页

作者： WANG HuaiMin DING Bo SHI DianXi CAO JianNong Alvin T.S.Chan National Key Laboratory of Parallel and Distributed Processing College of ComputerNational University of Defense Technology Department of Computing Hong Kong Polytechnic University

Adaptivity is the capacity of software to adjust itself to changes in its environment. A common approach to achieving adaptivity is to introduce dedicated code during software development stage. However,since those code fragments are designed a priori, self-adaptive software cannot handle situations adequately when the contextual changes go beyond those that are originally anticipated. In this case, the original builtin adaptivity should be tuned. For example, new code should be added to provide the capacity to sense the unexpected environment or to replace outdated adaptation decision logic. The technical challenges in this process, especially that of tuning software adaptivity at runtime, cannot be understated. In this paper,we propose an architecture-centric application framework for self-adaptive software named Auxo. Similar to existing work, our framework supports the development and running of self-adaptive software. Furthermore,our framework supports the tuning of software adaptivity without requiring the running self-adaptive software to be terminated. In short, the architecture style that we are introducing can encapsulate not only general functional logic but also the concerns in the self-adaptation loop(such as sensing, decision, and execution)as architecture elements. As a result, a third party, potentially the operator or an augmented software entity equipped with explicit domain knowledge, is able to dynamically and flexibly adjust the self-adaptation concerns through modifying the runtime software architecture. To truly exercise, validate, and evaluate our approach,we describe a self-adaptive application that was deployed on the framework, and conducted several experiments involving self-adaptation and the online tuning of software adaptivity.

关键词： software architecture self-adaptive software architecture style application framework software adaptation

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Combining FFT and Spectral-Pooling for Efficient Convolution Neural Network Model

Combining FFT and Spectral-Pooling for Efficient Convolution...

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2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE2016)

作者： Zelong Wang Qiang Lan Dafei Huang Mei Wen Department of Compute National University of Technology Defense National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology

ISBN: (纸本)9781510835368

Convolution operation is the most important and time consuming step in a convolution neural network *** this work,we analyze the computing complexity of direct convolution and fast-Fourier-transform-based(FFT-based) *** creatively propose CS-unit,which is equivalent to a combination of a convolutional layer and a pooling layer but more *** computing complexity of and some other similar operation is demonstrated,revealing an advantage on computation of ***,practical experiments are also performed and the result shows that CS-unit holds a real superiority on run time.

关键词： computing complexity FFT-based convolution CS-unit

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Fast garment simulation with aid of hybrid bones

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Journal of Central South University 2015年第6期22卷 2218-2226页

作者：吴博陈寅徐凯程志全熊岳山 College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory (National University of Defense Technology) Avatar Science Company

A data-driven method was proposed to realistically animate garments on human poses in reduced space. Firstly, a gradient based method was extended to generate motion sequences and garments were simulated on the sequences as our training data. Based on the examples, the proposed method can fast output realistic garments on new poses. Our framework can be mainly divided into offline phase and online phase. During the offline phase, based on linear blend skinning(LBS), rigid bones and flex bones were estimated for human bodies and garments, respectively. Then, rigid bone weight maps on garment vertices were learned from examples. In the online phase, new human poses were treated as input to estimate rigid bone transformations. Then, both rigid bones and flex bones were used to drive garments to fit the new poses. Finally, a novel formulation was also proposed to efficiently deal with garment-body penetration. Experiments manifest that our method is fast and accurate. The intersection artifacts are fast removed and final garment results are quite realistic.

关键词： data-driven linear blend skinning hybrid bones interactive

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An Architecture of parallel Tiled QRD Algorithm for MIMO-OFDM Systems

An Architecture of Parallel Tiled QRD Algorithm for MIMO-OFD...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Cang Liu Chuan Tang Zuocheng Xing Lirui Chen Yang Zhang Guitao Fu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Beijing Satellite Navigation Center Beijing China

ISBN: (纸本)9781509032068

The QR decomposition (QRD) has been extensively adopted in the transceiver processor of Multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The antenna configuration of future MIMO-OFDM system is very flexible. Therefore, the QRD architecture should also has the flexibility feature to decompose various dimensional channel response matrices. However, the existing QRD hardware architectures for MIMO-OFDM systems mainly focus on several fixed dimensional matrices. Due to the flexibility and scalability of parallel tiled QRD algorithm, it is very suitable for future MIMO-OFDM systems. A versatile hardware architecture (Ver_Arch) is designed for the bottleneck operations of parallel tiled QRD algorithm in this paper. Based on the designed Ver_Arch, we also design a QRD architecture for 4×4 real matrix. To the best of our knowledge, this is the first paper that presents a completed QRD hardware architecture based on the parallel tiled QRD algorithm for MIMO-OFDM wireless communication systems.

关键词： Matrix decomposition Hardware Algorithm design and analysis Computer architecture Wireless communication MIMO OFDM

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The Efficient In-band Management for Interconnect Network in Tianhe-2 System

The Efficient In-band Management for Interconnect Network in...

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Euromicro Conference on parallel, distributed and Network-Based processing

作者： Jijun Cao Liquan Xiao Zhengbin Pang Kefei Wang Jiaqing Xu College of Computer National University of Defense Technology China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology China

Interconnect network plays an important role in high performance computing systems. And its manageability directly affects the RAS (i.e., Reliability, Availability, and Serviceability) of the whole system. The Tianhe-2 system located in NSCC-gz (i.e., National Supercomputing Center of China in Guangzhou) uses proprietary interconnect network, which includes 5,856 high-radix network router chips (i.e., NRC) and 18,304 network interface chips (i.e., NIC). For such a very large-scale interconnect network, it is a great challenge to manage (such as configure, monitor, and debug) the numerous network chips and its network ports in an efficient way. By implementing the in-band management with very few hardware resources, the interconnect network in Tianhe-2 system achieves a highly efficient network management. In this paper, we introduce the design and implementation of the in-band management for interconnect network in Tianhe-2 system, especially emphasizing on several key features, including the set of achieved management functionalities, the architecture of network management, the format of management packets, the data flow and processing of management packets, etc. In this paper, we also evaluate the performance of in-band management by mainly comparing with out-band management scheme. The preliminary results demonstrate the efficiency of the in-band management for interconnect network in Tianhe-2 system.

关键词： Routing Ports (Computers) Network topology Optical switches Hardware Topology Registers

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High-performance Audio Matching with Features Learned by Convolutional Deep Belief Network

High-performance Audio Matching with Features Learned by Con...

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2016 IEEE 13th International Conference on Signal processing（ICSP2016）

作者： Weijiang Feng Naiyang Guan Zhigang Luo Institute of Software College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

Audio matching automatically retrieves all excerpts that have the same content as the query audio clip from given audio recordings. The extracted feature is critical for audio matching and the Chroma Energy Normalized Statistics(CENS) feature is the state-of-the-arts. However, CENS might behave unsatisfactorily on some audio because it is a handcraft feature. In this paper, we propose to utilize the features learned by Convolutional Deep Belief Network(CDBN) to enhance the performance of audio matching. Benefit from the strong generalization ability of CDBN, our method works better than CENS based methods on most audio datasets. Since the features learned by CDBN are binary-valued, we can develop a more efficient audio matching algorithm by taking the advantage of this property. Experimental results on both TIMIT dataset and a simulated music dataset confirm effectiveness of the proposed CDBN based method comparing with the traditional CENS feature based algorithm.

关键词： audio matching convolutional deep belief network content-based audio retrieval

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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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