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International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2021

作者： Wang, Kang Niu, Xin Dou, Yong Yang, Di Xie, Dongxing Yang, Tuo National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha410073 China Department of Orthopaedics Xiangya Hospital Central South University Changsha410008 China Department of Health Management Center Xiangya Hospital Central South University Changsha410008 China

ISBN: (纸本)9789811638794

Knee osteoarthritis (OA) is a common musculoskeletal illness. To solve the problem that inaccurate knee joint localization and inadequate knee OA features extracted from plain radiographs affect the accuracy of knee OA diagnosis in X-rays, we propose a novel Two-Stage Convolutional Neural Network (TS-CNN) method, consisting of the KneeDetnet and the KLnet. The KneeDetnet with two small multi-task convolutional neural networks is proposed to locate knee joints, improving the accuracy of knee joint localization. Then KLnet is designed to assess knee OA, where a shared Siamese network via ResNet is used to extract more discriminative deep learning features that are fused with gender information for obtaining richer features. Our method is evaluated on public OAI and MOST datasets. The highest detection accuracy of knee joints can reach 99.93% and 99.02% on two datasets, respectively. The KLnet algorithm achieves 78.85% and 68.20% prediction accuracy on the OAI and MOST datasets, respectively. Experimental results show that our method outperforms the existing workhorse. The proposed approach may become a potentially useful tool for assisting physicians. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks

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Toward Optimal Deployment of Communication-Intensive Cloud Applications

Toward Optimal Deployment of Communication-Intensive Cloud A...

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IEEE International Conference on Cloud Computing, CLOUD

作者： Pei Fan Ji Wang Zibin Zheng Michael R. Lyu National Laboratory for Parallel & Distributed Processing National University of Defense Technology Changsha China Department of Computer Science & Engineering Chinese University of Hong Kong Hong Kong China

Strongly promoted by the leading industrial companies, cloud computing becomes increasingly popular in re-cent years. The growth rate of cloud computing surpasses even the most optimistic predictions. A cloud application is a large-scale distributed system that consist a lot of distributed cloud nodes. How to make optimal deployment of cloud applications is a challenging research problem. When deploying a cloud application to the cloud environment, cloud node ranking is one of the most important approaches for selecting optimal cloud nodes for the cloud application. Traditional ranking methods usually rank the cloud nodes based on their QoS values, without considering the communication performance between cloud nodes. However, such kind of node relationship is very important for the communication-intensive cloud applications (e.g., Message Passing Interface (MPI) programs), which have a lot of communications between the selected cloud nodes. In this paper, we propose a novel clustering-based method for selecting optimal cloud nodes for deploying communication-intensive applications to the cloud environment. Our method not only takes into account the cloud node qualities, but also the communication performance between different nodes. We deploy several well-known MPI programs on a real-world cloud and compare our method with other methods. The experimental results show the effectiveness of our cluster-based method.

关键词： Time factors Cloud computing Benchmark testing Quality of service Servers Clustering algorithms Databases

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A compact analytical model for multi-island single electron transistors

A compact analytical model for multi-island single electron ...

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International Conference on ASIC

作者： Yaqing Chi Bingcai Sui Liang Fang Hailiang Zhou Haiqing Zhong He Sun National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Hunan China National University of Defense Technology Changsha Hunan CN

Multi-island single electron transistor (SET) has become a promising candidate for the kernel device of the logic circuit in the near future. A novel compact analytical model for multi-island SET is proposed in terms of current. The new approach is based on the orthodox theory of single electron tunnelling and steady-state master equation. The model is accurate and fast compared with SIMON, and suitable for the ASIC design of multi-island SET circuit simulation.

关键词： Analytical models Single electron transistors

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NR-MPI: A Non-stop and Fault Resilient MPI

NR-MPI: A Non-stop and Fault Resilient MPI

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International Conference on parallel and distributed Systems (ICPADS)

作者： Guang Suo Yutong Lu Xiangke Liao Min Xie Hongjia Cao 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, in particular in the perspective of future E-scale systems, which will consist of millions of CPU cores and other components. Fault tolerant MPI was proposed to offer support of software level fault tolerance approaches. However, the widely used MPI implementations, such as MPICH and Mvapich2, provide limited support for fault tolerance. This paper proposes NR-MPI, a Non-stop and Fault Resilient MPI. NR-MPI implements the semantics of FT-MPI based on MPICH. Specifically, this paper focuses on failure detection in MPI library, online failure recovery of communicators for multiple failures, friendly programming interface extending for NR-MPI. Furthermore, to support failure recovery of applications, NR-MPI implements data backup and restore interfaces based on double in-memory checkpoint/restart. We conduct experiments with NPB benchmarks on TH-1A supercomputer. 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.

关键词： Fault tolerance Fault tolerant systems Libraries Resource management Context Programming Semantics

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A distributed approach to consistent order delivery of concurrent events in asynchronous DVEs

ICETC 2010 - 2010 2nd International Conference on Education ...

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ICETC 2010 - 2010 2nd International Conference on Education technology and Computer 2010年 4卷 V495-V498页

作者： Zhou, Hangjun Zhang, Wei Peng, Yuxing Li, Sikun 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 410073 China Department of Information Management Hunan College of Finance and Economics Changsha Hunan 410205 China

ISBN: (纸本)9781424463688

In large-scale asynchronous distributed virtual environments(DVEs), one of the difficult problems is to deliver the concurrent events in a consistent order at each node. Generally, the previous consistency control approaches can be classified into two categories: causal order and time stamped order. However, causal order approaches can merely preserve the cause-effect relation of events and time stamped order approaches seem intrinsically complex to be used in serverless large-scale asynchronous DVEs. In this paper, we proposed a novel distributed algorithm to identify the concurrent events and preserve the consistent order delivery of them at different nodes. Simulation studies are also carried out to compare the performance of this algorithm with that of the previous ones. The results show that the new algorithm can effectively deliver the concurrent events in consistent order at each node and is more efficient than the previous algorithms in large-scale asynchronous DVEs. © 2010 IEEE.

关键词： Virtual reality

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Proposing an intelligent mesh smoothing method with graph neural networks

arXiv

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arXiv 2023年

作者： Wang, Zhichao Chen, Xinhai Yan, Junjun Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology National University of Defense Technology Changsha410073 China

In CFD, mesh smoothing methods are commonly utilized to refine the mesh quality to achieve high-precision numerical simulations. Specifically, optimization-based smoothing is used for high-quality mesh smoothing, but it incurs significant computational overhead. Pioneer works improve its smoothing efficiency by adopting supervised learning to learn smoothing methods from high-quality meshes. However, they pose difficulty in smoothing the mesh nodes with varying degrees and also need data augmentation to address the node input sequence problem. Additionally, the required labeled high-quality meshes further limit the applicability of the proposed method. In this paper, we present GMSNet, a lightweight neural network model for intelligent mesh smoothing. GMSNet adopts graph neural networks to extract features of the node's neighbors and output the optimal node position. During smoothing, we also introduce a fault-tolerance mechanism to prevent GMSNet from generating negative volume elements. With a lightweight model, GMSNet can effectively smoothing mesh nodes with varying degrees and remain unaffected by the order of input data. A novel loss function, MetricLoss, is also developed to eliminate the need for high-quality meshes, which provides a stable and rapid convergence during training. We compare GMSNet with commonly used mesh smoothing methods on two-dimensional triangle meshes. The experimental results show that GMSNet achieves outstanding mesh smoothing performances with 5% model parameters of the previous model, and attains 13.56 times faster than optimization-based smoothing. © 2023, CC BY.

关键词： Graph neural networks

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An Online/Offline HIBS Scheme for Privacy Protection of People-centric Sensing

An Online/Offline HIBS Scheme for Privacy Protection of Peop...

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International Conference on Industrial Informatics, Computing technology, Intelligent technology, Industrial Information Integration (ICIICII)

作者： Peixin Chen Xiaofeng Wang Jinshu Su College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467383134

People-Centric Sensing (PCS), which collects information closely related to human activity and interactions in societies, is stepping into a flourishing time. Along with its great benefits, PCS poses new security challenges such as data integrity, participant privacy. Hierarchical Identity-Based Signature (HIBS) scheme can efficiently provide high integrity messaging, secure communication and privacy protection to PCS. However, the low computation efficiency primarily hinders the PCS adoption of HIBS scheme. In this paper, we propose an online/offline HIBS (HIBOOS) scheme for securing PCS. By splitting the signing phase into online and offline procedures, our scheme achieves high signing efficiency.

关键词： Games Sensors Privacy Public key Generators Wireless sensor networks

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distributed Line Graphs: A Universal Framework for Building DHTs Based on Arbitrary Constant-Degree Graphs

Distributed Line Graphs: A Universal Framework for Building ...

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International Conference on distributed Computing Systems

作者： Yiming Zhang Ling Liu Dongsheng Li Xicheng Lu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Georgia Institute of Technology College of Computing Georgia Institute of Technology Atlanta USA

ISBN: (纸本)9781424431748

Most proposed DHTs have their unique maintenance mechanisms specific to the static graphs on which they are based. In this paper we propose distributed line graphs (DLG), a universal framework for building DHTs based on arbitrary constant-degree graphs. We prove that in a DLG-enabled, N-node DHT, the out-degree is d, the in-degree is between 1 and 2d, and the diameter is less than 2(log d N-log d N 0 +D 0 +1), where d, D 0 and N 0 represent the degree, diameter and number of nodes of the initial graph, respectively. The maintenance cost of DLG-enabled DHTs is O(log d N). We show the power of DLG technique by applying it to Kautz graphs to propose a new DHT scheme.

关键词： Routing Maintenance engineering Buildings Distance measurement Topology Industries Construction industry

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An Intelligent Broker Approach to Semantics-Based Service Composition

An Intelligent Broker Approach to Semantics-Based Service Co...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Yufeng Zhang Hong Zhu National Laboratory for Parallel and Distributed Processing Department of Computing Science National University of Defense Technology Changsha China Department of Computing and Electronics Oxford Brookes University Oxford UK

This paper proposes an intelligent broker approach to service composition and collaboration. The broker employs a planner to generate service composition plans according to service usage and workflow knowledge, dynamically searches for services according to the plan, then invokes and coordinates the executions of the selected services at runtime. A prototype called I-Broker has been implemented to support the approach, which can be instantiated by populating the knowledge-base with domain specific knowledge to form domain specific brokers. This paper also reports experiments that evaluate the scalability of the approach.

关键词： Knowledge based systems Ontologies Semantics Complexity theory Planning Scalability Prototypes

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Modeling Full Information with Graph Network for Joint Entity-Relation Extraction 21

Modeling Full Information with Graph Network for Joint Entit...

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Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence

作者： Qian Wan Luona Wei Xinhai Chen Jie Liu Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology China College of Systems Engineering National University of Defense Technology China Laboratory of Software Engineering for Complex Systems National University of Defense Technology China

ISBN: (纸本)9781450385053

Fully capturing contextual information and analyzing the association between entity semantics and type is helpful for joint extraction task: 1) The context can reflect the part of speech and semantics of entity. 2) The entity type is closely related to the relation between entities. Previous research used to simply embed the contextual information into shallow layer of the model, ignoring the association between entity semantics and type. In this paper, we propose a graph network with full-information modeling to explicitly model different-level information in the text. The contextual information of entity is dynamically embedded in each span representation to improve the reasoning ability. To capture the fine-grained association between the semantics and type of entity, the graph network uses the feature of entity types to generate edge information between different nodes. Experimental results show that our model outperforms previous models on the CoNLL04 dataset and obtains competitive results on the SciERC dataset in both entity recognition and relation extraction. Extensive additional experiments further verify the effectiveness of the model.

关键词： Natural Language processing Named Entity Recognition Graph Network Deep Learning Relation Extraction

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