检索结果-内蒙古大学图书馆

33rd International Conference on Advanced Information Networking and Applications, AINA 2019

作者： Zheng, Li-ming Long, Wen-feng Liu, Yu-Jia Sun, Wei-dong Department of Message Communication Armed Police Officer Academy Chengdu China National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9783030150341

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. © 2019, Springer Nature Switzerland AG.

关键词： Routing algorithms

来源：评论

学校读者我要写书评

暂无评论

Secure and Fast Decision Tree Evaluation on Outsourced Cloud Data 2nd

Secure and Fast Decision Tree Evaluation on Outsourced Cloud...

引用

2nd International Conference on Machine Learning for Cyber Security, ML4CS 2019

作者： Liu, Lin Su, Jinshu Chen, Rongmao Chen, Jinrong Sun, Guangliang Li, Jie School of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China National University of Defense Technology Changsha China

ISBN: (纸本)9783030306182

Decision trees are famous machine learning classifiers which have been widely used in many areas, such as healthcare, text classification and remote diagnostics, etc. The service providers usually host a decision tree model on the cloud server and provide some classification service for clients to use such a model remotely. In such a scenario, the model is a valuable asset to the cloud which should not be disclosed to the clients, while the query data and classification results are private to the client. To solve such a problem, we propose several building blocks, i.e., secure comparison and secure polynomial calculation, in a two-cloud model. Based on these building blocks, we design a privacy-preserving decision tree evaluation scheme. Compared with the most recent works, our scheme can fully protect the tree model and clients’ data privacy simultaneously. Besides, our scheme also supports offline service users which is essential to the system’s scalability. Moreover, through theoretical analysis and real-world experimental test, it is oblivious that our scheme is quite efficient. © 2019, Springer Nature Switzerland AG.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Deep reinforcement learning for combinatorial optimization: Covering salesman problems

arXiv

引用

arXiv 2021年

作者： Li, Kaiwen Zhang, Tao Wang, Rui Wang, Yuheng Han, Yi College of Systems Engineering National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology HKL-MSI2T Changsha410073 China Graduate College National University of Defense Technology Changsha410073 China Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

This paper introduces a new deep learning approach to approximately solve the Covering Salesman Problem (CSP). In this approach, given the city locations of a CSP as input, a deep neural network model is designed to directly output the solution. It is trained using the deep reinforcement learning without supervision. Specifically, in the model, we apply the Multi-head Attention to capture the structural patterns, and design a dynamic embedding to handle the dynamic patterns of the problem. Once the model is trained, it can generalize to various types of CSP tasks (different sizes and topologies) with no need of re-training. Through controlled experiments, the proposed approach shows desirable time complexity: it runs more than 20 times faster than the traditional heuristic solvers with a tiny gap of optimality. Moreover, it significantly outperforms the current state-of-the-art deep learning approaches for combinatorial optimization in the aspect of both training and inference. In comparison with traditional solvers, this approach is highly desirable for most of the challenging tasks in practice that are usually large-scale and require quick decisions. Copyright © 2021, The Authors. All rights reserved.

关键词： Combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

A mesh quality discrimination method based on convolutional neural network

A mesh quality discrimination method based on convolutional ...

引用

IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Zhenpeng Xu Xinhai Chen Lihua Chi Jie Liu Chunye Gong Science and Technology on Parallel and Distributed Processing Laboratory & Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170060

With the rapid development of highperformance computing, computational fluid dynamics (CFD) has become an important part of hydrodynamics and aerodynamics. Mesh quality is the key factor that affects the accuracy and efficiency of CFD numerical calculation. However, the current the process of mesh quality discrimination is very time-consuming. The manpower time needed for this process takes up a large proportion in the whole numerical calculation process. A large number of artificial intelligence algorithms have been put forward to replace the human to efficiently complete all kinds of tedious tasks. In this paper, we propose a convolutional neural network (CNN) based mesh quality discrimination method, MeshNet. MeshNet uses residual neural network structure to learn mesh features and automatically judge the mesh quality. The experimental results show that the proposed network can greatly save labor time cost and achieve an accuracy of 94.41% for mesh quality discrimination.

关键词： Convolution Computational fluid dynamics Convolutional neural networks Jacobian matrices Artificial intelligence distributed processing Software engineering

来源：评论

学校读者我要写书评

暂无评论

Efficient Management and Intelligent Fault Tolerance for HPC Interconnect Networks

Efficient Management and Intelligent Fault Tolerance for HPC...

引用

International Conference on parallel and distributed Systems (ICPADS)

作者： Jijun Cao Mingche Lai Zhang Luo jiaqing Xu Zhengbin Pang College of Computer National Laboratory for Parallel and Distributed Processing ChangSha China

ISBN: (纸本)9781728125848

Interconnect Network is the key component in high performance computing system. With the incoming era of Exa-Scale (10 18 FLOPS) computing, designing large scale interconnect networks is facing with serious challenges in network management and fault tolerance. To construct higher performance and more reliable interconnect networks, we propose an efficient and intelligent network management architecture for indirect interconnect networks. This paper emphatically introduces the network management architecture, the in-band management channels in the Network Interface Chips (NIC) and Network Routing Chips (NRC) respectively, efficient centralized network management approach, distributed intelligent faulttolerant routing management, and so on. Based on the prototype system, the Control and Status Registers (CSR) accessing latency performance of in-band network management is evaluated. Also based on a customized simulation model for indirect interconnect networks, the typical distributed fault-tolerant scenes are tested. The experiment results show the in-band network management can averagely achieves 716 times improvements than the out of-band network management. Moreover, by running heuristic algorithms to automatically reconstruct routing tables for failure links or routers, the intellectual network management Engine can achieve fault-tolerant routing to maximizing network performance.

关键词： High performance computing system Interconnect network Network management Fault tolerate Network management Fault tolerance High Performance Computing unified network management architecture Network Network routing

来源：评论

学校读者我要写书评

暂无评论

Word-level BERT-CNN-RNN Model for Chinese Punctuation Restoration

Word-level BERT-CNN-RNN Model for Chinese Punctuation Restor...

引用

International Conference on Computer and Communications (ICCC)

作者： Zhe Zhang Jie Liu Lihua Chi Xinhai Chen Science and Technology on Parallel and Distributed Processing Laboratory & Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Punctuation restoration in speech recognition has a wide range of application scenarios. Despite the widespread success of neural networks methods at performing punctuation restoration for English, there have been only limited attempts for Chinese punctuation restoration. Due to the differences between Chinese and English in terms of grammar and basic semantic units, existing methods for English is not suitable for Chinese punctuation restoration. To tackle this problem, we propose a hybrid model combining the kernel of Bidirectional Encoder Representations from Transformers (BERT), Convolution Neural Network (CNN) and Recurrent Neural Network (RNN). This model employs a flexible structure and special CNN design which can extract word-level features for Chinese language. We compared the performance of the hybrid model with five widely-used punctuation restoration models on the public dataset. Experimental results demonstrate that our hybrid model is simple and efficient. It outperforms other models and achieves an accuracy of 69.1%.

关键词： Recurrent neural networks Computational modeling Bit error rate Semantics Speech recognition Feature extraction Task analysis

来源：评论

学校读者我要写书评

暂无评论

A Heterogeneous Processor Design for CNN-Based AI Applications on IoT Devices

引用

Procedia Computer Science 2020年 174卷 2-8页

作者： Zhiqiang Liu Jingfei Jiang Guoqing Lei Kai Chen Buyue Qin Xiaoqiang Zhao Artificial Intelligence Research Center National Innovation Institute of Defense Technology Beijing China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China College of System Engineering National University of Defense Technology Changsha China

This paper proposes a heterogeneous processor design for CNN-based AI applications on IoT devices. The heterogeneous processor contains an embedded RISC-V CPU that works as a general processor and an efficient CNN-accelerator that supports a variety of CNN models with a list of macro instructions. For demonstration, we implement a prototype on an FPGA platform with the RISC-V CPU working under 20 MHz and the CNN accelerator working under 100 MHz. As a case study, we run a CNN-based face detection and recognition application on this prototype. The prototype can process one image in 0.72 seconds and an ASIC implementation working under 400 MHz can process one image in less than 0.15 seconds by estimation, which can satisfy the needs for many IoT scenarios such as access control systems and check-in systems.

关键词： Processor RISC-V Accelerator AI (Artificial Intelligence) CNN (Convolutional Neural Network) IoT (Internet of Things)

来源：评论

学校读者我要写书评

暂无评论

Software Effective Evaluating Technology: SWEET

Software Effective Evaluating Technology: SWEET

引用

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Yaozong Li Tao Wang Yue Yu Dongyang Hu National Laboratory for Parallel and Distributed Processing National University of Defence Technology Changsha China

ISBN: (数字)9781728109459

ISBN: (纸本)9781728109466

In open source community, there are a large number of software resources existing. Such software resources distribute in different societies or storehouses, which require different software characteristic. This phenomenon results in difficult to evaluate software quality using traditional methods. In this case, a novel open-source software sorting algorithm may be an effective solution. Considering both subjective and objective levels, we propose a new method on software sorting and retrieving. In the subjective level, metrics are selected from the corresponding collaborative development community based on software topic. In the objective level, metrics are obtained from the group emotional evaluation value of the knowledge sharing community. We have proved the effectiveness of the method through comparison experiments. Combining with the Solrcloud tool, this method has been integrated into the OSSEAN platform.

关键词： Open source software Sorting Collaboration Software algorithms Measurement Tools

来源：评论

学校读者我要写书评

暂无评论

An Efficient High-Precision Data Detection for Massive MU-MIMO Systems

An Efficient High-Precision Data Detection for Massive MU-MI...

引用

International Conference on Electronic Engineering and Informatics (EEI)

作者： Shikai Qiu Yu Wang Lirui Chen Zuocheng Xing National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha Hunan

ISBN: (纸本)9781728140773

Data detection is among the most crucial process task for massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems. In this letter, we propose a novel efficient high precision soft-output data detection algorithm, which iteratively generates a signal vector and reduces its complexity meanwhile. This algorithm guarantees its significant error-rate performance and reduced complexity by combing an optimization method, ADMM, and modified neighborhood search algorithm. Simulation results demonstrate that the proposed detection achieves superior performance over the existing methods at low computational complexity.

关键词： computational complexity MIMO communication multi-access systems optimisation search problems signal detection Multi access systems MIMO communication tabu search complexity classes signal acquisition data detection multiple input multiple output systems

来源：评论

学校读者我要写书评

暂无评论

Algorithm and architecture for path metric aided bit-flipping decoding of polar codes

arXiv

引用

arXiv 2019年

作者： Wang, Yu Chen, Lirui Wang, Qinglin Zhang, Yang Xing, Zuocheng National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

Polar codes attract more and more attention of researchers in recent years, since its capacity achieving property. However, their error-correction performance under successive cancellation (SC) decoding is inferior to other modern channel codes at short or moderate blocklengths. SC-Flip (SCF) decoding algorithm shows higher performance than SC decoding by identifying possibly erroneous decisions made in initial SC decoding and flipping them in the sequential decoding attempts. However, it performs not well when there are more than one erroneous decisions in a codeword. In this paper, we propose a path metric aided bit-flipping decoding algorithm to identify and correct more errors efficiently. In this algorithm, the bit-flipping list is generated based on both log likelihood ratio (LLR) based path metric and bit-flipping metric. The path metric is used to verify the effectiveness of bit-flipping. In order to reduce the decoding latency and computational complexity, its corresponding pipeline architecture is designed. By applying these decoding algorithm and pipeline architecture, an improvement on error-correction performance can be got up to 0.25dB compared with SCF decoding at frame error rate of 10−4, with low average decoding latency. Copyright © 2019, The Authors. All rights reserved.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：