检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

4,281 篇 会议
47 篇 期刊文献
3 册 图书

馆藏范围

4,331 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,432 篇 工学
- 2,168 篇 计算机科学与技术...
- 1,080 篇 软件工程
- 607 篇 电气工程
- 586 篇 信息与通信工程
- 185 篇 仪器科学与技术
- 138 篇 控制科学与工程
- 120 篇 电子科学与技术（可...
- 64 篇 生物工程
- 59 篇 机械工程
- 43 篇 动力工程及工程热...
- 38 篇 交通运输工程
- 31 篇 生物医学工程（可授...
- 27 篇 安全科学与工程
- 26 篇 网络空间安全
- 24 篇 光学工程
- 23 篇 土木工程
- 22 篇 材料科学与工程（可...
- 20 篇 建筑学
- 19 篇 航空宇航科学与技...
418 篇 理学
- 253 篇 数学
- 86 篇 物理学
- 72 篇 生物学
- 51 篇 系统科学
- 42 篇 统计学（可授理学、...
261 篇 管理学
- 179 篇 管理科学与工程(可...
- 97 篇 图书情报与档案管...
- 65 篇 工商管理
35 篇 医学
- 30 篇 临床医学
33 篇 法学
- 19 篇 社会学
18 篇 经济学
- 18 篇 应用经济学
11 篇 农学
7 篇 教育学
7 篇 文学
2 篇 军事学
1 篇 艺术学

主题

543 篇 parallel process...
259 篇 computer archite...
238 篇 computational mo...
207 篇 distributed comp...
186 篇 concurrent compu...
179 篇 computer network...
164 篇 network topology
157 篇 hardware
157 篇 graphics process...
148 篇 routing
130 篇 bandwidth
123 篇 application soft...
120 篇 neural networks
120 篇 protocols
107 篇 scalability
104 篇 multicore proces...
103 篇 throughput
102 篇 algorithm design...
102 篇 kernel
101 篇 computer science

机构

15 篇 institute of inf...
14 篇 institute of com...
14 篇 science and tech...
13 篇 college of compu...
13 篇 school of cyber ...
13 篇 shandong fundame...
12 篇 school of comput...
10 篇 science and tech...
9 篇 univ chinese aca...
9 篇 university of ch...
9 篇 natl univ def te...
9 篇 natl univ def te...
8 篇 shenyang aerospa...
8 篇 beijing univ pos...
8 篇 nanjing univ aer...
8 篇 beijing universi...
7 篇 shanghai jiao to...
7 篇 college of compu...
7 篇 chinese acad sci...
7 篇 national key lab...

作者

17 篇 bagherzadeh nade...
16 篇 kotenko igor
14 篇 j. duato
12 篇 wang yijie
11 篇 daneshtalab maso...
10 篇 ebrahimi masoume...
10 篇 yijie wang
10 篇 nader bagherzade...
10 篇 igor kotenko
10 篇 lexi xu
9 篇 li dongsheng
9 篇 marco aldinucci
9 篇 matsutani hiroki
8 篇 hiroki matsutani
8 篇 masoumeh ebrahim...
8 篇 plosila juha
8 篇 marco danelutto
8 篇 wang huaimin
7 篇 tenhunen hannu
7 篇 xinzhou cheng

语言

4,273 篇 英文
49 篇 其他
11 篇 中文
1 篇 乌克兰文

检索条件"任意字段=Euromicro Conference on Parallel, Distributed and Network-Based Processing"

共 4331 条记录，以下是671-680 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Fast and scalable in-network lock management using lock fission 24

Fast and scalable in-network lock management using lock fiss...

引用

Proceedings of the 18th USENIX conference on Operating Systems Design and Implementation

作者： Hanze Zhang Ke Cheng Rong Chen Haibo Chen Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Shanghai AI Laboratory and MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Shanghai AI Laboratory and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China and Key Laboratory of System Software (Chinese Academy of Sciences)

ISBN: (纸本)9781939133403

distributed lock services are extensively utilized in distributed systems to serialize concurrent accesses to shared resources. The need for fast and scalable lock services has become more pronounced with decreasing task execution times and expanding dataset scales. However, traditional lock managers, reliant on server CPUs to handle lock requests, experience significant queuing delays in lock grant latency. Advanced network hardware (e.g. programmable switches) presents an avenue to manage locks without queuing delays due to their high packet processing power. Nevertheless, their constrained memory capacity restricts the manageable lock scale, thereby limiting their effect in large-scale *** paper presents FISSLOCK, a fast and scalable distributed lock service that exploits the programmable switch to improve (tail) latency and peak throughput for millions of locks. The key idea behind FISSLOCK is the concept of lock fission, which decouples lock management into grant decision and participant maintenance. FISSLOCK leverages the programmable switch to decide lock grants synchronously and relies on servers to maintain participants (i.e., holders and waiters) asynchronously. By using the programmable switch for routing, FISSLOCK enables on-demand fine-grained lock migration, thereby reducing the lock grant and release delays. FISSLOCK carefully designs and implements grant decision procedure on the programmable switch, supporting over one million locks. Evaluation using various benchmarks and a real-world application shows the efficiency of FISSLOCK. Compared to the state-of-the-art switch-based approach (NetLock), FISSLOCK cuts up to 79.1% (from 43.0%) of median lock grant time in the microbenchmark and improves transaction throughput for TATP and TPC-C by 1.76× and 2.28×, respectively.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Migration for Efficient Near-Data processing

Machine Learning Migration for Efficient Near-Data Processin...

引用

euromicro conference on parallel, distributed and network-based processing

作者： Aline S. Cordeiro Sairo R. dos Santos Francis B. Moreira Paulo C. Santos Luigi Carro Marco A. Z. Alves Federal University of Paraná Curitiba Brazil Federal Rural University of Semi-arid Angicos Brazil Informatics Institute Federal University of Rio Grande do Sul Porto Alegre Brazil

Machine Learning (ML) rises as a highly useful tool to analyze the vast amount of data generated in every field of science nowadays. Simultaneously, data movement inside computer systems gains more focus due to its high impact an time and energy consumption. In this context, the Near-Data processing (NDP) architectures emerged as a prominent solution to increasing data by drastically reducing the required amount of data movement For NDP, we see three main approaches, Application-Specific Integrated Circuits (ASICs), full Central processing Units (CPUs) and Graphics processing Units (GPIIs), or vector units integration. However, previous work considered only ASICs, CPUs and GPUs when executing ML algorithms inside the memory. In this paper, we present an approach to execute ML algorithms near-data, using a general-purpose vector architecture and applying near-data parallelism to kernels from KNN, MEP, and CNN algorithms. To facilitate this process, we also present an NDP intrinsics library to ease the evaluation and debugging tasks. Our results show speedups up to fox for KNN, 11× for MLP, and 3× for convolution when processing near-data compared to a high-performance ×86 baseline.

关键词： Integrated circuits Machine learning algorithms Graphics processing units Machine learning Computer architecture Tools parallel processing

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning-based network Moving Target Defense in DPDK

Deep Reinforcement Learning-based Network Moving Target Defe...

引用

IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Ke Shang Weizhen He Shuai Zhang Zhen Zhang Jichao Xie Xin Shi Institute of Information Technology Information Engineering University Zhengzhou China

Aiming at the problems of difficult deployment, high latency, and serious performance loss of current network moving target defense, this paper designs a network moving target defense system based on deep reinforcement learning by using Data Plane Development Kit (DPDK). In the paper, we first give the framework of the network moving target defense system based on DPDK. On this basis, in order to reduce the performance loss caused by shuffling network attributes, we design a performance model based on queuing theory and security model based on probability. In addition, we construct the relationship between performance and security by increasing the weighting factor, and then design the shuffling policy selection method based on the Proximal Policy Optimization algorithm. Simulation experimental results show that the optimal shuffling period obtained by the proposed algorithm can effectively enhance the security of the system and reduce the performance loss of the system. This method improves performance and security by 96% and 60%, respectively, compared to the comparison methods. In addition, the real environment verifies that the system can enhance the anti-scanning ability of the system while ensuring stable data transmission.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on the Design of Digital Signal processing Algorithm based on Spark parallel Calculation

Research on the Design of Digital Signal Processing Algorith...

引用

International conference on Electronics, Electrical and Information Engineering 2021, ICEEIE 2021

作者： Ming, Yifan Li, Rui School of Physics and Electronics Central South University Hunan China School of Mathematics and Computational Science Hunan University of Science and Technology Hunan China

Digital signal processing as a key and difficult point of network technology research and development, currently commonly used content such as LabVIEW. But from a practical point of view, while these techniques can be used to process real-time signals, they can't handle historical offline data. The Spark parallel computing studied in this paper can be used to process offline signals. Therefore, on the basis of understanding the development trend of Spark parallel computing framework, the distributed Mallat algorithm is analyzed based on Spark parallel computing engine, and the application performance of the corresponding algorithm is verified. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Digital signal processing

来源：评论

学校读者我要写书评

暂无评论

Improved Virtual Force Algorithm-based Fuzzy Clustering in Mobile Wireless Sensor networks

Improved Virtual Force Algorithm-Based Fuzzy Clustering in M...

引用

IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Jintao Yang Minghua Wang Wenbo Chen Shujing Xie School of Electrical Engineering University of South China Hengyang China

With the rapid development of wireless sensor networks(WSNs), Mobile Wireless Sensor networks (MWSNs) are receiving increased attention. MWSNs affect the performance of clustered networks, such as coverage and lifetime. In order to improve the coverage and the lifetime, this paper proposed fuzzy clustering method based on improved virtual force algorithm (IVFA-FC).IVFA-FC improves the network coverage and equalizes the distances between nodes through improved virtual force. Fuzzy clustering analyses multiple factors for selecting cluster head (CH) that change due to MWSN, so IVFA-FC uses fuzzy logic to optimize CH selection,to reduce the energy consumption of the network and to extend the network lifetime. In the experiments IVFA-FC is compared with the traditional virtual force algorithm and random wandering algorithm, IVFA-FC is effective in prolonging network lifetime,saving energy and improving coverage.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Competency Evaluation of Vocational Undergraduate Students based on multi-layer ER Rules

Comprehensive Competency Evaluation of Vocational Undergradu...

引用

Information Science, parallel and distributed Systems (ISPDS), International conference on

作者： Shukun Jin Xingyu Mu Guangdong Vocational and Technical University of Business and Technology Zhaoqing Guangdong China Jilin Province Meteorological Information Network Center Changchun Jilin China

Aiming at the problems in the evaluation of the comprehensive ability of vocational undergraduates and analyze the requirements of vocational undergraduates for the comprehensive ability of college students, study the problems of the index system and existing methods for evaluation problems, and propose a model for assessing the comprehensive ability of vocational undergraduates based on multilayer evidential reasoning rules. Evidential reasoning rule is an intelligent information fusion algorithm developed and extended based on Dempster-Shafer evidence theory, which can deal with the problems of diversifying evaluation information, describing the uncertainty of assessment information, and considering the reliability of evaluation information. The model firstly analyzes diversified information using natural language processing methods and standardizes it using rule/utility methods to realize data analysis and mining of diversified information; secondly, it uses hierarchical analysis and mathematical statistics methods to solve the weight and reliability of indicator information; finally, it realizes the fusion of diversified information based on evidence-based inference rules to evaluate the comprehensive ability of vocational undergraduates. The model is multilevel and interpretable, and can realize the combination of stage evaluation and result evaluation. Validate the effectiveness of the method through case study.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Requester-Provider Bilateral Utility Maximization and Collision Resistance in Blockchain-based Microgrid Energy Trading 21st

Towards Requester-Provider Bilateral Utility Maximization an...

引用

21st International conference on Algorithms and Architectures for parallel processing (ICA3PP)

作者： Wang, Hailun Zhang, Kai Wei, Lifei Zhang, Lei Shanghai Univ Elect Power Coll Comp Sci & Technol Shanghai Peoples R China Shanghai Ocean Univ Coll Informat Technol Shanghai Peoples R China

ISBN: (纸本)9783030953911;9783030953904

Microgrid is a promising system for coordinating distributed energy in the future Energy Internet, where energy market is crucial for facilitating multi-directional trading. Nevertheless, the traditional solutions for energy trading usually rely on a centralized framework, which is vulnerable to high operation cost and low transparency. To address the problem, the blockchain strategy has been widely deployed in microgrid energy trading. However, existing blockchain-based systems have not formally considered: (i) collusion attacks launched by a pair of dishonest consumer and microgrid;(ii) and the demands of maximizing bilateral utility. Therefore, in this work, we propose a blockchain-based microgrid energy trading system that allows a consumer to dynamically change its service quality quotes for a microgrid. In particular, bilateral utility of requester-provider is almost maximized, with employing a Bayesian Nash equilibrium strategy to model the interaction between consumers and microgrids. Moreover, collusion attacks during the bidding process are certainly prevented from a dishonest pair of consumer and microgrid. To achieve this, we employ a request-based comparable encryption technique to compare two microgrids' revenues in a privacy-preserving way, in which each microgrid should submit an encrypted expected revenue. In addition, a general security analysis of our system is formally discussed. To illustrate the effectiveness, we take a blockchain-based framework to build the experiment platform, where the structure of nodes and transaction process are well formalized.

关键词： Blockchain Microgrid Energy trading Bilateral utility Collision resistance

来源：评论

学校读者我要写书评

暂无评论

Leaf: Learning-based Stream-level Fair Scheduling for Deep Learning Accelerators

Leaf: Learning-based Stream-level Fair Scheduling for Deep L...

引用

International conference on parallel and distributed Systems (ICPADS)

作者： Yida Wang Bojun Cao Mengjuan Gao Qinwen Shi Yuanchao Xu College of Information Engineering Capital Normal University Beijing China State Key Lab of Processors ICT CAS Beijing China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Deep learning accelerators, as the cornerstone of machine learning systems, expedite neural network training and inference. With their computational power escalating annually, multi-tasking becomes imperative to harness their full potential. However, similar to other parallel processing systems, deep learning accelerators confront the problem of performance fluctuations which could result in unpredictable kernel latency, suboptimal resource utilization, and exacerbated tail latency. This paper identifies the unfairness in stream-level scheduling as the root cause of these performance fluctuations. To mitigate this issue, we introduce Leaf, an innovative learning-based stream-level fair scheduling method that dynamically learns and adapts scheduling policies by leveraging feature vectors extracted from enqueued kernels and accelerator status. To tackle the issue of scalability and latency constraints inherent in stream-level scheduling, we devise a scalable scheduling framework and an online scheduler switching mechanism for Leaf. Preliminary implementation on a commercial grade deep learning accelerator demonstrates that Leaf can significantly reduce kernel latency variation by $10 \sim 20$ times, sustain high and stable resource utilization, and markedly decrease workload runtime by mitigating tail latency, outperforming the accelerator’s native scheduler.

关键词： Deep learning Fluctuations Runtime Scalability Tail Switches Feature extraction Resource management Kernel Hardware acceleration

来源：评论

学校读者我要写书评

暂无评论

Scalable and Flexible High-Performance In-network processing of Hash Joins in distributed Databases 20

Scalable and Flexible High-Performance In-Network Processing...

引用

20th International conference on Field-Programmable Technology (ICFPT)

作者： Wirth, Johannes Hofmann, Jaco A. Thostrup, Lasse Binnig, Carsten Koch, Andreas Tech Univ Darmstadt Embedded Syst & Applicat Grp Darmstadt Germany Tech Univ Darmstadt Data Management Lab Darmstadt Germany

ISBN: (纸本)9781665420105

Programmable switches allow to offload specific processing tasks into the network and promise multi-Tbit /s throughput. One major goal when moving computation to the network is typically to reduce the volume of network traffic, and thus improve the overall performance. In this manner, programmable switches are increasingly used, both in research as well as in industry applications, for various scenarios, including statistics gathering, in-network consensus protocols, and more. However, the currently available programmable switches suffer from several practical limitations. One important restriction is the limited amount of available memory, making them unsuitable for stateful operations such as Hash Joins in distributed databases. In previous work, an FPGA-based In-network Hash Join accelerator was presented, initially using DDR-DRAM to hold the state. In a later iteration, the hash table was moved to on-chip HBM-DRAM to improve the performance even further. However, while very fast, the size of the joins in this setup was limited by the relatively small amount of available HBM. In this work, we heterogeneously combine DDR-DRAM and HBM memories to support both larger joins and benefit from the far faster and more parallel HBM accesses. In this manner, we are able to improve the performance by a factor of 3x compared to the previous HBM-based work. We also introduce additional configuration parameters, supporting a more flexible adaptation of the underlying hardware architecture to the different join operations required by a concrete use-case.

关键词： HBM FPGA Hash Join INP In-network processing

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Graph-Sequence Anomaly Detection for 5G Core network Control Plane Traffic

Unsupervised Graph-Sequence Anomaly Detection for 5G Core Ne...

引用

International conference on parallel and distributed Systems (ICPADS)

作者： Min Wang Peng Li Zhang Cheng Wenmao Liu Lei Nie Haizhou Bao Qin Liu Kai Zhang School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System China NSFOCUS Technologies Group Co. Ltd School of Cyber Science and Engineering Wuhan University China

5G Core network (5GC) employs a Service based Architecture (SBA). This architecture decomposes the control plane into multiple independent network Functions (NFs). NFs open interfaces to provide services to other NFs, which makes the control plane more susceptible to external malicious attacks. However, existing anomaly detection methods focus more on traffic statistics features and are difficult to apply to the 5GC control plane. In this paper, we proposed GSAD, a Graph-Sequence analysis-based Anomaly Detection method for 5GC control plane traffic. We model control plane traffic as a directed graph to depict topological and NF interaction information. Further, we use the normalizing flows with temporal dependencies to mine the sequential information in the traffic. GSAD combines the topological and sequential information to provide fine-grained detection. We evaluate our proposed framework on the 5GC testbed using Free5GC and UERANSIM in various scenarios. Experimental results demonstrate that our framework outperforms the baselines significantly in terms of detection performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共434页 << < 64 65 66 67 68 69 70 71 72 73 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：