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International Conference on Machine Learning and Applications (ICMLA)

作者： Xiang Zhang Naiyang Guan Zhigang Luo Xuejun Yang College of Computer National University of Defense Technology Changsha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China The State key Laboratory of High Performance Computing National University of Defense Technology Changsha China

This paper formulates multi-label learning as a constrained projective non-negative matrix factorization (CPNMF) problem which concentrates on a variant of the original projective NMF (PNMF) and explicitly introduces an auxiliary basis to learn the semantic subspace and boosts its discriminating ability by exploiting labeled and unlabeled examples together. Particularly, it propagates labels of the labeled examples to the unlabeled ones by enforcing coefficients of examples sharing identical semantic contents to be identical based on a hard constraint, i.e., embedding the class indicator of labeled examples into their coefficients. CPNMF preserves the geometrical structure of dataset via manifold regularization meanwhile captures the inherent structure of labels by using label correlations. We developed a multiplicative update rule (MUR) based algorithm to optimize CPNMF and proved its convergence. Experiments of image annotation on Corel dataset, text categorization on Rcv1v2 dataset, and text clustering on two popular text corpuses suggest the effectiveness of CPNMF.

关键词： Conferences

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Breaking Ties of Plurality Voting in Ensembles of distributed Neural Network Classifiers Using Soft Max Accumulations

IFIP Advances in Information and Communication Technology

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IFIP Advances in Information and Communication Technology 2014年 436卷 20-28页

作者： Kokkinos, Yiannis Margaritis, Konstantinos G. Parallel and Distributed Processing Laboratory Department of Applied Informatics University of Macedonia 156 Egnatia str. P.O. Box 1591 Thessaloniki54006 Greece

An ensemble of distributed neural network classifiers is composed when several different individual neural networks are trained based on their local training data. These classifiers can provide either a single class label prediction, or the normalized via the soft max real value class-outputs that represent posterior probabilities which give the confidence levels. To form the ensemble decision the individual classifier decisions can be combined via the well known majority (or plurality) voting that sums the votes for each class and selects the class that receives most of the votes. While the majority voting is the most popular combination rule many ties in votes can occur, especially in multi-class problems. Ties are usually broken either randomly where the unknown instance is assigned randomly to one of the tied classes or using the class proportions where the tied class with the largest proportion wins. We present a tie breaking strategy that uses soft max confidence accumulations. Every class accumulates a vote and a confidence for this vote. If a tie occurs then the tied class with the maximum confidence sum wins. The proposed tie breaking in the voting process performs very well in all cases of different data distributions on various benchmark datasets. © IFIP International Federation for Information processing 2014.

关键词： distributed computer systems

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Accelerating FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture

Accelerating FDTD simulation of microwave pulse coupling int...

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IEEE Pacific Rim Conference on Communications, Computers and Signal processing

作者： Qinglin Wang Jie Liu Xiantao Cui Guitao Fu Chunye Gong Zuocheng Xing School of Computer Science National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Beijing Satellite Navigation Center Beijing China

ISBN: (纸本)9781467377898

The coupling of microwaves into apertures plays an important part in many electromagnetic physics and engineering fields. When the width of apertures is very small, Finite Difference Time Domain (FDTD) simulation of the coupling is very time-consuming. As a many-core architecture, the Intel's Many Integrated Core (MIC) architecture owns 512-bit vector units and more than 200 threads. In this paper, we parallelize FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture. In the implementation, the parallel programming model OpenMP is used to exploit thread parallelism while loop unrolling and SIMD intrinsic functions are utilized to accomplish vectorization. Compared with the serial version on Intel Xeon E5-2670 CPU, the implementation on the MIC coprocessor including 57 cores obtains a speedup of 11.57 times. The experiment results also demonstrate that the parallelization has good scalability in performance. Additionally, how binding relationship between OpenMP threads and hardware threads in MIC influences performance is also reported.

关键词： Microwave integrated circuits Finite difference methods Time-domain analysis Chlorine Hardware

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Iaso： an autonomous fault-tolerant management system for supercomputers

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Frontiers of Computer Science 2014年第3期8卷 378-390页

作者： Kai LU Xiaoping WANG Gen LI Ruibo WANG Wanqing CHI Yongpeng LIU Hongwei TANG Hua FENG Yinghui GAO Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China College of Computer National University of Defense Technology Changsha 410073 China ATR Laboratory National University of Defense Technology Changsha 410073 China

With the increase of system scale, the inherent reliability of supercomputers becomes lower and lower. The cost of fault handling and task recovery increases so rapidly that the reliability issue will soon harm the usability of supercomputers. This issue is referred to as the ＂reliability wall＂, which is regarded as a critical problem for current and future supercomputers. To address this problem, we propose an autonomous fault-tolerant system, named Iaso, in MilkyWay- 2 system. Iaso introduces the concept of autonomous management in supercomputers. By autonomous management, the computer itself, rather than manpower, takes charge of the fault management work. Iaso automatically manage the whole lifecycle of faults, including fault detection, fault diagnosis, fault isolation, and task recovery. Iaso endows the autonomous features with MilkyWay-2 system, such as self-awareness, self-diagnosis, self-healing, and self-protection. With the help of Iaso, the cost of fault handling in supercomputers reduces from several hours to a few seconds. Iaso greatly improves the usability and reliability of MilkyWay-2 system.

关键词： supercomputer autonomous management fault tolerant fault management MilkyWay-2 system

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Unsupervised feature learning for human activity recognition using smartphone sensors 2

Unsupervised feature learning for human activity recognition...

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2nd International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2014

作者： Li, Yongmou Shi, Dianxi Ding, B. Liu, Dongbo National Key Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9783319138169

Feature representation has a significant impact on human activity recognition. While the common used hand-crafted features rely heavily on the specific domain knowledge and may suffer from nonadaptability to the particular dataset. To alleviate the problems of handcrafted features, we present a feature extraction framework which exploits different unsupervised feature learning techniques to learning useful feature representation from accelerometer and gyroscope sensor data for human activity recognition. The unsupervised learning techniques we investigate include sparse auto-encoder, denoising auto-encoder and *** evaluate the performance on a public human activity recognition dataset and also compare our method with traditional features and another way of unsupervised feature learning. The results show that the learned features of our framework outperform the other two methods. The sparse auto-encoder achieves better results than other two techniques within our framework. © Springer International Publishing Switzerland 2014.

关键词： Signal encoding

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NVLAN: A Novel VLAN Technology for Scalable Multi-tenant Datacenter Networks 2

NVLAN: A Novel VLAN Technology for Scalable Multi-tenant Dat...

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2nd International Conference on Advanced Cloud and Big Data, CBD 2014

作者： Hu, Yang Li, Huiba Peng, Yuxing Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Computer Science Department China

ISBN: (纸本)9781479980857

Nowadays, cloud providers of 'Infrastructure as a service' require datacenter networks to support virtualization and multi-tenancy at large scale, while it brings a grand challenge to datacenters. Traditional network technologies of datacenters and common commodity devices of network can not meet these new needs. In this paper, we present NVLAN, a novel VLAN technology for scalable multi-tenant datacenter networks. NVLAN eliminates the quantity limitation of logic isolated networks on VLAN through a slight modification. NVLAN can be applied to very large-scale datacenter networks, without the need of expensive and dedicated switches. Through encapsulation of tenant's packets, NVLAN provides tenants with full address space virtualization to configure their own logic network. We implemented NVLAN on a test bed, and demonstrated that it can be scaled up to large numbers of multi-tenant networks with negligible overhead. © 2014 IEEE.

关键词： Virtualization

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CRAWL: A Trace Routing Algorithm Based on Hybrid Two-Layer Topology

CRAWL: A Trace Routing Algorithm Based on Hybrid Two-Layer T...

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International Conference on Computer Sciences and Applications (CSA)

作者： Li-Ming Zheng Xiao-Dong Tan Wei-Dong Sun Xiao-Dong Li Department of Electronics Technology Armed Police Officer Academy Chengdu China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Ministry of Scientific Research Armed Police Officer Academy Chengdu China

ISBN: (纸本)9781479999620

Data distribution is a key technology for resources convergence and sharing in distributed environment. To better meet the requirement for real time data distribution in the dynamic network, a trace routing algorithm named CRAWL based on the hybrid two-layered topology is put forward. The algorithm contains an overlay topology named CBDLO, upper of which consists of multiple distributed balanced binary trees corresponding to different properties and the lower of which is an unstructured topology. CRAWL forwards the data on the lower unstructured topology in the form of random walk, so that the data can be sent to the corresponding upper topology entry, It also includes a matching algorithm named CDM for the parallel matching data properties on the upper distributed and balanced binary tree and transmitting the matched data to the nodes that are interested in the data. The experimental results show that the algorithm can effectively support large-scale data distribution in a dynamical network, reduce distribution overhead and matching delays.

关键词： Topology Peer-to-peer computing Routing distributed databases Network topology Heuristic algorithms Binary trees

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Exploring the patterns of social behavior in Github 1

Exploring the patterns of social behavior in Github

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1st International Workshop on Crowd-Based Software Development Methods and Technologies, CrowdSoft 2014

作者： Yu, Yue Yin, Gang Wang, Huaimin Wang, Tao National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450332248

Social coding paradigm is reshaping the distributed soft- ware development with a surprising speed in recent years. Github, a remarkable social coding community, attracts a huge number of developers in a short time. Various kinds of social networks are formed based on social activities among developers. Why this new paradigm can achieve such a great success in attracting external developers, and how they are connected in such a massive community, are interesting questions for revealing power of social coding paradigm. In this paper, we firstly compare the growth curves of project and user in GitHub with three traditional open source software communities to explore differences of their growth modes. We find an explosive growth of the users in GitHub and introduce the Diffusion of Innovation theory to illustrate intrinsic sociological basis of this phenomenon. Secondly, we construct follow-networks according to the follow behaviors among developers in GitHub. Finally, we present four typical social behavior patterns by mining follow-networks containing independence-pattern, group-pattern, star-pattern and hub-pattern. This study can provide several instructions of crowd collaboration to newcomers. According to the typical behavior patterns, the community manager could design corresponding assistive tools for developers. Copyright 2014 ACM.

关键词： Software design

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Improving vertex-frontier based GPU breadth-first search

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Journal of Central South University 2014年第10期21卷 3828-3836页

作者：杨博卢凯高颖慧徐凯王小平程志权 Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology College of Computer National University of Defense Technology Department of Electronic Science and Engineering National University of Defense Technology Avatar Science Company

Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.

关键词： breadth-first search GPU graph traversal vertex frontier

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Design and Implementation of a Highly Efficient DGEMM for 64-Bit ARMv8 Multi-core Processors

Design and Implementation of a Highly Efficient DGEMM for 64...

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International Conference on parallel processing (ICPP)

作者： Feng Wang Hao Jiang Ke Zuo Xing Su Jingling Xue Canqun Yang School of Computer Science National University of Defense Technology Changsha China School of Computer Science and Engineering University of New South Wales NSW Australia Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

This paper presents the design and implementation of a highly efficient Double-precision General Matrix Multiplication (DGEMM) based on Open BLAS for 64-bit ARMv8 eight-core processors. We adopt a theory-guided approach by first developing a performance model for this architecture and then using it to guide our exploration. The key enabler for a highly efficient DGEMM is a highly-optimized inner kernel GEBP developed in assembly language. We have obtained GEBP by (1) maximizing its compute-to-memory access ratios across all levels of the memory hierarchy in the ARMv8 architecture with its performance-critical block sizes being determined analytically, and (2) optimizing its computations through exploiting loop unrolling, instruction scheduling and software-implemented register rotation and taking advantage of A64 instructions to support efficient FMA operations, data transfers and prefetching. We have compared our DGEMM implemented in Open BLAS with another implemented in ATLAS (also in terms of a highly-optimized GEBP in assembly). Our implementation outperforms the one in ALTAS by improving the peak performance (efficiency) of DGEMM from 3.88 Gflops (80.9%) to 4.19 Gflops (87.2%) on one core and from 30.4 Gflops (79.2%) to 32.7 Gflops (85.3%) on eight cores. These results translate into substantial performance (efficiency) improvements by 7.79% on one core and 7.70% on eight cores. In addition, the efficiency of our implementation on one core is very close to the theoretical upper bound 91.5% obtained from micro-benchmarking. Our parallel implementation achieves good performance and scalability under varying thread counts across a range of matrix sizes evaluated.

关键词： Registers Kernel Computational modeling Program processors Assembly Memory management

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