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International Conference on computer science and Information Technology (CSIT)

作者： Hangjun Zhou Wei Zhang Yuxing Peng Sikun Li Department of Information Management Hunan College of Finance and Economics Changsha Hunan China Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan China

How to preserve causal and totally ordered event delivery is an important issue in real-time serverless DVE(Distributed Virtual Environment). However, most of the related works are designed to maintain causal order merely or time stamped order with intensive computation and bandwidth overhead. In this paper, we proposed a novel distributed algorithm to maintain the before-and-after relationship between events, both causal and concurrent, of DVE at each individual node. Several simulation experiments are carried out to evaluate the performance of our algorithm and the results demonstrate that the algorithm is effective in preserving causal and totally ordered event delivery and more efficient than the previous algorithms.

关键词： Artificial neural networks Silicon Educational institutions

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Gain-scheduling Distributed MPC for Polytopic Uncertain systems subject to Actuator Saturation

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IFAC Proceedings Volumes 2013年第13期46卷 444-449页

作者： Langwen Zhang Jingcheng Wang Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

In this paper, we present a gain-scheduling distributed model predictive control (MPC) algorithm for polytopic uncertain systems subject to actuator saturation. A large-scale system is decomposed into subsystems and sub-controllers are designed independently. An invariant set condition is provided and a min-max distributed MPC strategy is proposed based on the invariant set. The distributed MPC controller is determined by solving a linear matrix inequality (LMI) optimization problem. An iterative algorithm is provided to coordinate the sub-controllers. A numerical example is carried out to demonstrate the effectiveness of the proposed algorithm.

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A causality based dynamic message ordering for DVEs on Wide Area Network

A causality based dynamic message ordering for DVEs on Wide ...

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International Conference on Communication Software and Networks, ICCSN

作者： Hangjun Zhou Sha Fu Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan China Department of Information Management Hunan University of Finance and Economics Changsha Hunan China

Due to the large message transmission latency in Distributed Virtual Environments(DVEs) on Wide Area Net-work(WAN), the effectiveness of causality consistency control of message ordering is determined by not only causal order of messages but also the real-timeness. If merely causal order is considered, the real-time property of DVEs may not be ensured because of the unlimited waiting time for the delayed messages. While if only real-timeness is emphasized, there may be too many delayed messages, which have to be discarded, to maintain the quality of causal message ordering. Therefore, a trade-off between the quality of causal order delivery and real-timeness is necessary for DVEs. In this article, a novel causality based message ordering approach is presented. In general, this new approach dynamically balances the demands of causal order delivery and real-timeness. Experiment results demonstrate the approach can enhance the quality of causality, while simultaneously keep the real-time property of DVEs.

关键词： Educational institutions

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Protein 3D Features and surface modeling research

Protein 3D Features and surface modeling research

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2015 3rd International Conference on Machinery,Materials and Information Technology Applications(ICMMITA 2015)

作者： Huayong Yang Xiaoli Lin Information and Engineering Department of City College Wuhan University of Science and Technology Hubei Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Computer Science and Technology Wuhan University of Science and Technology

In the twenty-first century, the life science has been studied from the genome research into the structure and function of the structure, which can further reveal the mystery of life. In this paper, it takes the relationship between protein structure and its function as the breakthrough point, with the aid of introducing the protein molecular structure database, analyzing the application of intelligent computing method in the prediction of protein structure. Moreover, by setting up the 3D model of protein molecules, so as to realize the detection of protein 3D features.

关键词： protein molecular intelligent computing 3D features

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Approximate Maximum Common Sub-graph Isomorphism Based on Discrete-Time Quantum Walk

Approximate Maximum Common Sub-graph Isomorphism Based on Di...

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International Conference on Pattern Recognition

作者： Kai Lu Yi Zhang Kai Xu Yinghui Gao Richard C. Wilson Science and Technology on Parallel and Distributed Processing Laboratory and College of Computer National University of Defense Technology Changsha P.R. China College of Electronic Science and Engineering National University of Defense Technology Changsha P.R. China Department of Computer Science University of York York UK

Maximum common sub-graph isomorphism (MCS) is a famous NP-hard problem in graph processing. The problem has found application in many areas where the similarity of graphs is important, for example in scene matching, video indexing, chemical similarity and shape analysis. In this paper, a novel algorithm Qwalk is proposed for approximate MCS, utilizing the discrete-time quantum walk. Based on the new observation that isomorphic neighborhood group matches can be detected quickly and conveniently by the destructive interference of a quantum walk, the new algorithm locates an approximate solution via merging neighborhood groups. Experiments show that Qwalk has better accuracy, universality and robustness compared with the state-of-the-art approximate MCS methods. Meanwhile, Qwalk is a general algorithm to solve the MCS problem approximately while having modest time complexity.

关键词： Approximation algorithms Interference Algorithm design and analysis Accuracy Time complexity Quantum computing Noise

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Generic Face Animation

Generic Face Animation

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computer science Society (SCCC) International Conference Chilean FLAGGED

作者： Mauricio Cerda Renato Valenzuela Nancy Hitschfeld-Kahler Lucas D. Terissi Juan C. Gómez INRIA-Loria Nancy Grand Est Vandoeuvre-les-Nancy France Department of Computer Science Universidad de Chile Santiago Chile Laboratory for System Dynamics and Signal Processing CIFASIS CONICET Universidad Nacional de Rosario Rosario Argentina Laboratory for System Dynamics and Signal Processing CONICET Rosario Argentina

In computer vision, the animation of objects has attracted a lot of attention, specially the animations of 3D face models. The animation of face models requires in general to manually adapt each generic movement (open/close mouth) to each specific head geometry. In this work we propose a technique for the animation of any face model avoiding most of the manual intervention. In order to achieve this we assume that: (1) faces, despite obvious differences are quite similar and a single generic model can be used to simplify deformations and (2) using this face model, a simple interpolation technique can be used, with minimal manual intervention. Several examples are presented to verify the realism of the obtained animations.

关键词： Animation Three dimensional displays Face Deformable models Interpolation Solid modeling Adaptation model

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Domain-invariant similarity activation map contrastive learning for retrieval-based long-term visual localization

arXiv

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arXiv 2020年

作者： Hu, Hanjiang Wang, Hesheng Liu, Zhe Chen, Weidong Autonomous Robot Lab Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory of Robotics and System HIT The Department of Computer Science and Technology University of Cambridge United Kingdom

Visual localization is a crucial component in the application of mobile robot and autonomous driving. Image retrieval is an efficient and effective technique in image-based localization methods. Due to the drastic variability of environmental conditions, e.g. illumination, seasonal and weather changes, retrieval-based visual localization is severely affected and becomes a challenging problem. In this work, a general architecture is first formulated probabilistically to extract domain-invariant feature through multi-domain image translation. And then a novel gradient-weighted similarity activation mapping loss (Grad-SAM) is incorporated for finer localization with high accuracy. We also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised manner. The final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models without and with Grad-SAM loss. Extensive experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons dataset. The strong generalization ability of our approach is verified on RobotCar dataset using models pre-trained on urban part of CMU-Seasons dataset. Our performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision, especially under the challenging environments with illumination variance, vegetation and night-time images. The code and pretrained models are available on https://***/HanjiangHu/DISAM. Copyright © 2020, The Authors. All rights reserved.

关键词： Image retrieval

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An Energy-Efficient Scheduling Algorithm for Sporadic Real-Time Tasks in Multiprocessor systems

An Energy-Efficient Scheduling Algorithm for Sporadic Real-T...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Dong-Song Zhang Fang-Yuan Chen Hong-Hua Li Shi-Yao Jin De-Ke Guo National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China School of Computing Science Simon Fraser University Burnaby BC Canada National Laboratory for Information System Engineering School of Information Systems and Management National University of Defense Technology Changsha China

As the energy consumption of embedded multiprocessor systems becomes increasingly prominent, the real-time energy-efficient scheduling in multiprocessor systems becomes an urgent problem to reduce the system energy consumption while meeting real-time constraints. For a multiprocessor with independent DVFS and DPM at each processor, this paper proposes an energy-efficient real-time scheduling algorithm named LRE-DVFS-EACH, based on LRE-TL which is an optimal real-time scheduling algorithm for sporadic tasks. LRE-DVFS-EACH utilizes the concept of TL plane and the idea of fluid scheduling to dynamically scale the voltage and frequency of processors at the initial time of each TL plane as well as the release time of a sporadic task in each TL plane. Consequently, LRE-DVFS-EACH can obtain a reasonable tradeoff between the real-time constraints and the energy saving. LRE-DVFS-EACH is also adaptive to the change of workload caused by the dynamic release of sporadic tasks, which can obtain more energy savings. The experimental results show that compared with existing algorithms, LRE-DVFS-EACH can not only guarantee the optimal feasibility of sporadic tasks, but also achieve more energy savings in all cases, especially in the case of high workloads.

关键词： Real time systems Scheduling algorithm Time frequency analysis Scheduling Heuristic algorithms Power demand

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NUMA-aware FFT-based convolution on ARMv8 many-core CPUs

arXiv

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arXiv 2021年

作者： Huang, Xiandong Wang, Qinglin Lu, Shuyu Hao, Ruochen Mei, Songzhu Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China School of Computer Science National University of Defense Technology Changsha410073 China Department of Biomedical Informatics University of Pittsburgh Pittsburgh United States

Convolutional Neural Networks (CNNs), one of the most representative algorithms of deep learning, are widely used in various artificial intelligence applications. Convolution operations often take most of the computational overhead of CNNs. The FFT-based algorithm can improve the efficiency of convolution by reducing its algorithm complexity, there are a lot of works about the high-performance implementation of FFT-based convolution on many-core CPUs. However, there is no optimization for the non-uniform memory access (NUMA) characteristics in manycore CPUs. In this paper, we present a NUMA-aware FFT-based convolution implementation on ARMv8 many-core CPUs with NUMA architectures. The implementation can reduce a number of remote memory access through the data reordering of FFT transformations and the three-level parallelization of the complex matrix multiplication. The experiment results on a ARMv8 many-core CPU with NUMA architectures demonstrate that our NUMA-aware implementation has much better performance than the state-of-the-art work in most cases. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

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科学研究的第五范式——以智能驱动的材料设计为例

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Engineering 2023年第5期24卷 126-137,I0003,I0004页

作者： Can Leng Zhuo Tang Yi-Ge Zhou Zean Tian Wei-Qing Huang Jie Liu Keqin Li Kenli Li Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410073China Laboratory of Software Engineering for Complex Systems National University of Defense TechnologyChangsha 410073China National Supercomputing Center in Changsha Changsha 410082China College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China Institute of Chemical Biology and Nanomedicine State Key Laboratory of Chemo/Biosensing and ChemometricsCollege of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China Department of Applied Physics School of Physics and ElectronicsHunan UniversityChangsha 410082China Department of Computer Science State University of New YorkNew PaltzNY 12561USA

科学正在进入一个新时代——第五范式——它被认为是知识整合到不同领域的主要特征,是基于无所不在的机器学习系统的计算社区中智能驱动的工作。在此,我们通过在天河一号超级计算机系统上构建的催化材料专门设计的典型平台案例,生动地... 详细信息

科学正在进入一个新时代——第五范式——它被认为是知识整合到不同领域的主要特征,是基于无所不在的机器学习系统的计算社区中智能驱动的工作。在此,我们通过在天河一号超级计算机系统上构建的催化材料专门设计的典型平台案例,生动地阐明了第五范式的本质,旨在促进第五范式在其他领域的培养。第五范式平台主要包括模型自动构建(原始数据提取)、指纹自动构建(神经网络特征选择)以及跨学科知识串联的重复迭代(“火山图”)。与分解一起进行的是对迭代中实现的体系结构的性能评估。通过讨论,第五范式的智能驱动平台可以极大地简化和改进研究中极其繁琐和具有挑战性的工作,并通过补偿机器学习中缺少样本和替代一些由于计算资源不足而导致的数值计算来实现数值计算与机器学习之间的相互反馈,从而加速探索过程。在数据驱动的学科中,跨学科专家的协同作用和对动态数据需求的急剧增长仍然是一个挑战。我们相信,对第五范式平台的一瞥可以为其在其他领域的应用铺平道路。

关键词：机器学习自动构建天河一号数据驱动神经网络动态数据知识整合科学研究

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