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Internet-based virtual computing environment(iVCE):Concepts and architecture

science in China(Series F) 2006年第6期49卷 681-701页

作者： LU Xicheng WANG Huaimin WANG Ji National Laboratory for Parallel and Distributed Processing Changsha 410073 China College of Computer National University of Defense Technology Changsha 410073 China

Resources over Internet have such intrinsic characteristics as growth, autonomy and diversity, which have brought many challenges to the efficient sharing and comprehensive utilization of these resources. This paper presents a novel approach for the construction of the Internet-based Virtual Computing Environment （iVCE）, whose sig- nificant mechanisms are on-demand aggregation and autonomic collaboration. The iVCE is built on the open infrastructure of the Internet and provides harmonious, transparent and integrated services for end-users and applications. The concept of iVCE is presented and its architectural framework is described by introducing three core concepts, i.e., autonomic element, virtual commonwealth and virtual executor. Then the connotations, functions and related key technologies of each components of the architecture are deeply analyzed with a case study, iVCE for Memory.

关键词： resource aggregation collaboration virtual computing environment Internet

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Labelwalking nonnegative matrix factorization 40

Labelwalking nonnegative matrix factorization

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40th IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2015

作者： Lan, Long Guan, Naiyang Zhang, Xiang Huang, Xuhui Luo, Zhigang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781467369978

Semi-supervised learning (SSL) utilizes plenty of unlabeled examples to boost the performance of learning from limited labeled examples. Due to its great discriminant power, SSL has been widely applied to various real-world tasks such as information retrieval, pattern recognition, and speech separa- tion. Label propagation (LP) is a popular SSL method which propagates labels through the dataset along high density areas defined by unlabeled examples, LP assumes nearby examples should share the same label, thus, it unavoidably pushes the labels to the wrong examples, especially when different la- beled examples are not strictly separated. Seed K-means uses labeled examples to initialize class centers, and avoid getting stuck in poor local optima comparing to traditional K-means, however the hard constraint of each example's membership makes Seed K-means failed in many real world applications. This paper proposes a novel label walking nonnegative matrix factorization method (LWNMF) to handle labeled examples in SSL based on the framework of NMF. LWNMF decomposes the whole dataset into the product of a basis matrix and a coefficient matrix, and to travel labels to unlabeled examples, LWNMF regards the class indicators of labeled examples as their coefficients and iteratively updates both basis matrix and coefficients of unlabeled examples. Since LWNMF learns comprehensive class centroids, labels iteratively walk to unlabeled examples through these significant centroids. © 2015 IEEE.

关键词： K-means Label propagation Nonnegative matrix factorization Semisupervised learning

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Large-scale virtual machines provisioning in clouds： challenges and approaches

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Frontiers of Computer science 2016年第1期10卷 2-18页

作者： Zhaoning ZHANG Dongsheng LI Kui WU National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China Computer Science Department University of Victoria Victoria V8W 2Y2 Canada

The scale of global data center market has been explosive in recent years. As the market grows, the demand for fast provisioning of the virtual resources to support elas- tic, manageable, and economical computing over the cloud becomes high. Fast provisioning of large-scale virtual ma- chines （VMs）, in particular, is critical to guarantee quality of service （QoS）. In this paper, we systematically review the existing VM provisioning schemes and classify them in three main categories. We discuss the features and research status of each category, and introduce two recent solutions, VMThunder and VMThunder＋, both of which can provision hundreds of VMs in seconds.

关键词： cloud computing IaaS large scale virtual ma-chine provisioning

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Smoothing Point Adjustment-Based Evaluation of Time Series Anomaly Detection 48

Smoothing Point Adjustment-Based Evaluation of Time Series A...

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Liu, Mingyu Wang, Yijie Xu, Hongzuo Zhou, Xiaohui Li, Bin Wang, Yongjun National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory College of Computer Changsha China

ISBN: (纸本)9781728163277

Anomalies in time series appear consecutively, forming anomaly segments. Applying the classical point-based evaluation metrics to evaluate the detection performance of segments leads to considerable underestimation, so most related studies resort to point adjustment. This operation treats all points as true positives within a segment equally when only one individual point alarms, resulting in significant overestimation and creating an illusion of superior performance. This paper proposes smoothing point adjustment, a novel range-based evaluation protocol for time series anomaly detection. Our protocol reflects detection performance impartially by carefully considering the specific location and frequency of alarms in the raw results. It is achieved by smoothly determining the adjustment range and rewarding early detection via a ranging function and a rewarding function. Compared with other evaluation metrics, experiments on different datasets show that our protocol can yield a performance ranking of various methods more consistent with the desired situation. © 2023 IEEE.

关键词： Anomaly Detection Evaluation Protocol Point Adjustment Time Series

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CWLP:coordinated warp scheduling and locality-protected cache allocation on GPUs

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Frontiers of Information technology & Electronic Engineering 2018年第2期19卷 206-220页

作者： Yang ZHANG Zuo-cheng XING Cang LIU Chuan TANG National Laboratory for Parallel and Distributed Processing National University of Defense Technology

As we approach the exascale era in supercomputing, designing a balanced computer system with a powerful computing ability and low power requirements has becoming increasingly important. The graphics processing unit（GPU） is an accelerator used widely in most of recent supercomputers. It adopts a large number of threads to hide a long latency with a high energy efficiency. In contrast to their powerful computing ability, GPUs have only a few megabytes of fast on-chip memory storage per streaming multiprocessor（SM）. The GPU cache is inefficient due to a mismatch between the throughput-oriented execution model and cache hierarchy design. At the same time, current GPUs fail to handle burst-mode long-access latency due to GPU＇s poor warp scheduling ***, benefits of GPU＇s high computing ability are reduced dramatically by the poor cache management and warp scheduling methods, which limit the system performance and energy efficiency. In this paper, we put forward a coordinated warp scheduling and locality-protected（CWLP） cache allocation scheme to make full use of data locality and hide latency. We first present a locality-protected cache allocation method based on the instruction program counter（LPC） to promote cache performance. Specifically, we use a PC-based locality detector to collect the reuse information of each cache line and employ a prioritised cache allocation unit（PCAU） which coordinates the data reuse information with the time-stamp information to evict the lines with the least reuse possibility. Moreover, the locality information is used by the warp scheduler to create an intelligent warp reordering scheme to capture locality and hide latency. Simulation results show that CWLP provides a speedup up to 19.8% and an average improvement of 8.8% over the baseline methods.

关键词： Locality Graphics processing unit （GPU） Cache allocation Warp scheduling

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OHTMA:an optimized heuristic topology-aware mapping algorithm on the Tianhe-3 exascale supercomputer prototype

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Frontiers of Information technology & Electronic Engineering 2020年第6期21卷 939-949页

作者： Yi-shui LI Xin-hai CHEN Jie LIU Bo YANG Chun-ye GONG Xin-biao GAN Sheng-guo LI Han XU Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410073China

With the rapid increase of the size of applications and the complexity of the supercomputer architecture,topology-aware process mapping becomes increasingly *** communication cost has become a dominant constraint of the performance of applications running on the *** avoid a bad mapping strategy which can lead to terrible communication performance,we propose an optimized heuristic topology-aware mapping algorithm(OHTMA).The algorithm attempts to minimize the hop-byte metric that we use to measure the mapping *** incorporates a new greedy heuristic method and pair-exchange-based *** reduces the number of long-distance communications and effectively enhances the locality of the *** results on the Tianhe-3 exascale supercomputer prototype indicate that OHTMA can significantly reduce the communication costs.

关键词： High-performance computing Topology mapping Heuristic algorithm

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Guided Spatio-Temporal Learning Method for 4K Video Super-Resolution 5

Guided Spatio-Temporal Learning Method for 4K Video Super-Re...

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5th ACM International Conference on Multimedia in Asia, MMAsia 2023

作者： Jiang, Qin Wang, Qinglin Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology China

ISBN: (纸本)9798400702051

4K Video Super-Resolution (VSR) presents a challenging task in video processing, as most existing VSR models have high computational complexity, limiting their application to high-resolution videos, particularly for 4K resolution videos. To address this issue, we propose a novel Guided Spatio-Temporal Video Super-Resolution network (GST-VSR) designed to perform 4K VSR on a single GPU. The proposed method comprises two key components: the Spatio-Temporal Alignment Network (STAN) and the Super-resolution Reconstruction Network (SRN), which work together to enhance the quality of the output frames. The STAN is responsible for extracting highly relevant features in frames and aligning the reference frame with the neighboring frames at the feature level to maintain temporal consistency. The SRN fuses high-quality features into the final high-resolution frames. Unlike existing methods, our proposed approach does not require explicit optical flow estimation, making it more efficient and less computationally demanding. To facilitate the training and testing of the compared models, we have established a new dataset, Pixabay-Set, consisting of 145 videos suitable for the 4K VSR task. Experimental results on the test dataset show that the proposed method achieves competitive performance compared to state-of-the-art models. In summary, our proposed GST-VSR network provides an effective solution to the challenging task of 4K VSR. © 2023 Copyright held by the owner/author(s).

关键词： Statistical tests

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Memory access characterization of scientific applications on GPU and its implication on low power optimization

Memory access characterization of scientific applications on...

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2011 International Conference on Computational and Information sciences, ICCIS 2011

作者： Wang, Guibin National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

ISBN: (纸本)9780769545011

Following current IC design technology trend, modern GPUs integrate more and more processing cores, and the speed gap between processor and memory system becomes even larger. As the number of cores continually increases, the available bandwidth per core decreases correspondingly. Therefore, memory access performance has been one of the most critical bottlenecks for better performance. This paper analyzes the impact of memory system on performance and scalability for GPU with several scientific applications using a cycle-accurate simulator. Two observations we make are (1) that memory bandwidth has relatively greater impact on performance than memory latency, because the latter factor could be well hidden with tremendous concurrent executing threads supported in modern GPU architecture, and (2) that through examining the performance scalability of variable active cores, using the maximum hardware-supported cores may not bring in better performance, especially for the memory-intensive applications. In the end we suggest a better power-efficient exploitation of GPU is to make judicious concurrency-throttling based on the memory usage in application. © 2011 IEEE.

关键词： Graphics processing unit

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Adaptive Linearized Alternating Direction Method of Multipliers for Non-Convex Compositely Regularized Optimization Problems

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Tsinghua science and technology 2017年第3期22卷 328-341页

作者： Linbo Qiao Bofeng Zhang Xicheng Lu Jinshu Su College of Computer National University of Defense Technologyand National Laboratory for Parallel and Distributed ProcessingNational University of Defense TechnologyChangsha 410073China College of Computer National University of Defense TechnologyChangsha 410073China

We consider a wide range of non-convex regularized minimization problems, where the non-convex regularization term is composite with a linear function engaged in sparse learning. Recent theoretical investigations have demonstrated their superiority over their convex counterparts. The computational challenge lies in the fact that the proximal mapping associated with non-convex regularization is not easily obtained due to the imposed linear composition. Fortunately, the problem structure allows one to introduce an auxiliary variable and reformulate it as an optimization problem with linear constraints, which can be solved using the Linearized Alternating Direction Method of Multipliers （LADMM）. Despite the success of LADMM in practice, it remains unknown whether LADMM is convergent in solving such non-convex compositely regularized optimizations. In this research, we first present a detailed convergence analysis of the LADMM algorithm for solving a non-convex compositely regularized optimization problem with a large class of non-convex penalties. Furthermore, we propose an Adaptive LADMM （AdaLADMM） algorithm with a line-search criterion. Experimental results on different genres of datasets validate the efficacy of the proposed algorithm.

关键词： adaptive linearized alternating direction method of multipliers non-convex compositely regularizedoptimization cappled-ll regularized logistic regression

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Approximate Iteration Detection and Precoding in Massive MIMO

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China Communications 2018年第5期15卷 183-196页

作者： Chuan Tang Yerong Tao Yancang Chen Cang Liu Luechao Yuan Zuocheng Xing Luoyang Electronic Equipment Test Center LuoYang 471000China National Laboratory for Parallel and Distributed Processing National University of Defense TechnologyChangsha 410073China

Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection and precoding. Recently, many detection and precoding methods were proposed using approximate iteration methods, which meet the demand of precision with low complexity. In this paper, we compare these approximate iteration methods in precision and complexity, and then improve these methods with iteration refinement at the cost of little complexity and no extra hardware resource. By derivation, our proposal is a combination of three approximate iteration methods in essence and provides remarkable precision improvement on desired vectors. The results show that our proposal provides 27%-83% normalized mean-squared error improvement of the detection symbol vector and precoding symbol vector. Moreover, we find the bit-error rate is mainly controlled by soft-input soft-output Viterbi decoding when using approximate iteration methods. Further, only considering the effect on soft-input soft-output Viterbi decoding, the simulation results show that using a rough estimation for the filter matrix of minimum mean square error detection to calculating log-likelihood ratio could provideenough good bit-error rate performance, especially when the ratio of base station antennas number and the users number is not too large.

关键词： massive MIMO detection and precoding matrix inversion iteration refinement soft Viterbi decoding

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