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

23,957 篇 会议
411 篇 期刊文献
285 册 图书
1 篇 学位论文
1 篇 科技报告

馆藏范围

24,655 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

14,508 篇 工学
- 13,378 篇 计算机科学与技术...
- 5,960 篇 软件工程
- 2,508 篇 电气工程
- 2,169 篇 信息与通信工程
- 916 篇 控制科学与工程
- 531 篇 电子科学与技术（可...
- 412 篇 机械工程
- 327 篇 生物工程
- 261 篇 动力工程及工程热...
- 219 篇 仪器科学与技术
- 207 篇 生物医学工程（可授...
- 155 篇 材料科学与工程（可...
- 152 篇 力学（可授工学、理...
- 150 篇 建筑学
- 147 篇 土木工程
- 123 篇 网络空间安全
- 117 篇 环境科学与工程（可...
- 112 篇 交通运输工程
2,958 篇 理学
- 2,035 篇 数学
- 450 篇 物理学
- 396 篇 生物学
- 343 篇 系统科学
- 313 篇 统计学（可授理学、...
- 146 篇 化学
2,039 篇 管理学
- 1,503 篇 管理科学与工程(可...
- 712 篇 工商管理
- 668 篇 图书情报与档案管...
249 篇 医学
- 190 篇 临床医学
- 111 篇 基础医学(可授医学...
173 篇 经济学
- 172 篇 应用经济学
154 篇 法学
85 篇 农学
83 篇 教育学
41 篇 文学
11 篇 军事学
8 篇 艺术学

主题

2,979 篇 distributed comp...
1,753 篇 parallel process...
1,702 篇 concurrent compu...
1,630 篇 cloud computing
1,226 篇 computational mo...
1,084 篇 computer archite...
949 篇 grid computing
932 篇 computer science
791 篇 application soft...
753 篇 computer network...
615 篇 scalability
519 篇 distributed data...
515 篇 algorithm design...
512 篇 hardware
500 篇 peer to peer com...
497 篇 parallel algorit...
487 篇 high performance...
451 篇 software enginee...
451 篇 parallel computi...
439 篇 artificial intel...

机构

52 篇 university of ch...
41 篇 college of compu...
39 篇 institute of com...
37 篇 college of intel...
36 篇 department of co...
31 篇 department of co...
29 篇 school of comput...
28 篇 national laborat...
28 篇 natl univ def te...
27 篇 school of comput...
24 篇 school of comput...
24 篇 shandong provinc...
24 篇 institute of inf...
23 篇 institute of par...
22 篇 univ chinese aca...
21 篇 university of sc...
21 篇 school of comput...
20 篇 shanghai jiao to...
20 篇 department of co...
20 篇 school of comput...

作者

35 篇 li dongsheng
30 篇 liu jie
29 篇 dongsheng li
27 篇 duerr frank
26 篇 m. takizawa
26 篇 rajkumar buyya
26 篇 zomaya albert y.
24 篇 fahringer thomas
21 篇 jack dongarra
19 篇 yang yang
18 篇 li kenli
18 篇 wei li
18 篇 prodan radu
17 篇 wang guojun
17 篇 badia rosa m.
16 篇 liu yang
16 篇 p. banerjee
16 篇 dou yong
15 篇 lei wang
15 篇 xuejun yang

语言

24,330 篇 英文
224 篇 其他
87 篇 中文
17 篇 俄文
2 篇 土耳其文
2 篇 乌克兰文
1 篇 德文
1 篇 西班牙文
1 篇 法文

检索条件"任意字段=International Conference on Advances in Parallel and Distributed Computing"

共 24655 条记录，以下是541-550 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：

distributed Task Offloading Method Based on Federated Reinforcement Learning in Vehicular Networks with Incomplete Information 1

引用

23rd international conference on Algorithms and Architectures for parallel Processing (ICA3PP)

作者： Cao, Rui Song, Zhengchang Niu, Bingxin Gu, Junhua Li, Chunjie Hebei Univ Technol Sch Artificial Intelligence Tianjin Peoples R China Hebei Univ Technol Hebei Prov Key Lab Big Data Calculat Tianjin Peoples R China Hebei Expressway Grp Ltd Shijiazhuang Hebei Peoples R China

ISBN: (数字)9789819708598

ISBN: (纸本)9789819708581;9789819708598

With the development of Internet of Vehicles, a large number of different types of applications have emerged. However, given the limited computing power of vehicles, many tasks cannot be completed within specified time. The task offloading method based on mobile edge computing (MEC) effectively solves the problem. However, the existing research does not fully consider user needs and has the disadvantages of limited application scope and slow training speed, so it is not suitable for high-speed vehicle scenarios. Considering the heterogeneity of tasks and the different needs of users, this paper first designs a dynamic weighting method for delay and vehicle energy consumption, and then proposes a distributed algorithm FDQN based on Deep Q-Network (DQN) and federated learning. The algorithm does not require any information about the base station and can utilize user collaboration to achieve fast convergence. The experimental results show that our algorithm can achieve best optimization effect under different vehicle energy and speeds.

关键词： Task offloading Federated learning Vehicular network Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

An SGX and Blockchain-Based System for Federated Learning in Classifying COVID-19 Images 21

An SGX and Blockchain-Based System for Federated Learning in...

引用

21st IEEE international Symposium on parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Qin, Sihang Gu, Xianjun Jun, Xing Li, Haitao Huang, Mengqi Dai, Weiqi Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China State Grid Wuhan Power Supply Company China

ISBN: (纸本)9798350329223

Federated learning, an emerging distributed learning framework, has gained prominence recently. However, two challenges arise when applying federated learning to medical data. The first challenge stems from the inability of model-generating nodes to ensure computational fairness. The second challenge involves the potential leakage of private information through gradient differences. This paper introduces a federated learning system that leverages Software Guard Extensions (SGX) and blockchain technology to enhance the fairness and security of federated learning for analyzing chest imaging data. The modeling of imaging factors for chest radiography data can effectively regulate the data quality of semi-trusted nodes. A blockchain smart contract is employed for data quality-aware proof, and the quality-aware block undergoes a two-stage rewriting process across distinct nodes. A notary membership model achieves notarized cluster consensus for imaging informatics data. The multi-channel layer model quantifies the distribution of computational workload across participating nodes within the medical consortium. Upon successful verification of the enclave command in the aggregation cycle, traceable and packaged signatures are generated to support computational fairness. To ensure robust information security, SGX remote authentication is used between downstream and upstream nodes. The federated learning system, built upon SGX and blockchain, has been implemented using the Fabric federated chain platform. The ResNet model underwent training through cross-sectional federated learning to effectively classify novel coronavirus lung medical image data. Following this, multiple experimental control and security analyses were conducted, revealing that the time loss incurred due to crossing channels is approximately 21.31%, while the time overhead of SGX remains within 5.2%, as allowed by the number of nodes. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Joint Optimization of Model Partitioning and Resource Allocation for Edge computing with Intermittently Operating Devices 29

Joint Optimization of Model Partitioning and Resource Alloca...

引用

29th IEEE international conference on parallel and distributed Systems, ICPADS 2023

作者： Wu, Qi Zhang, Yi Yang, Chenxi Sun, Jin Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China

ISBN: (纸本)9798350330717

The new intermittent computing paradigm allows for intermittent operation of energy-harvesting devices, posing new challenges to edge intelligence in delivering high-quality computing services. This paper aims at the joint optimization of model partitioning and resource allocation for reducing the latency of deep neural network (DNN) applications on an edge computing system with intermittently operating devices. We establish a rigorous optimization model for the joint optimization problem that takes into account the heterogeneity and intermittent operation of end devices. Tailed for the inference procedure of DNN applications, we develop a family of partitioning rules for decomposing the DNN structure to facilitate computation offloading. We propose a model partitioning and resource allocation algorithm to determine the optimized assignment of computing resources for the DNN tasks offloaded from multiple devices onto the edge server. The proposed algorithm first utilizes the partitioning rules to obtain a preliminary decision on model partitioning, and introduces a greedy-based strategy to determine the final decision on the partitioning points of DNN structures as well as the amount of computing resources assigned for task execution. Simulation results on an edge system with heterogeneous devices, including Raspberry Pi 3B+, Raspberry Pi 4B, and Jetson Xavier NX, demonstrating that the proposed algorithm outperforms baseline methods with shorter latency when executing DNN inference tasks. © 2023 IEEE.

关键词： computation offloading edge intelligence intermittent computing model partitioning resource allocation

来源：评论

学校读者我要写书评

暂无评论

AshPipe: Asynchronous Hybrid Pipeline parallel for DNN Training 24

AshPipe: Asynchronous Hybrid Pipeline Parallel for DNN Train...

引用

7th international conference on High Performance computing in Asia-Pacific Region (HPC Asia)

作者： Hosoki, Ryubu Endo, Toshio Hirofuchi, Takahiro Ikegami, Tsutomu Tokyo Inst Technol Yokohama Kanagawa Japan Natl Inst Adv Ind Sci & Technol Tokyo Japan

ISBN: (纸本)9798400708893

Deep Neural Networks (DNNs) have become increasingly computationally intensive and have larger parameters, requiring efficient parallelization or distribution using multiple accelerators. Pipeline parallelism has been proposed as an effective way to distribute models and improve hardware utilization. However, the problem with pipeline parallelism is the trade-off between speedup and accuracy: synchronous approaches do not provide sufficient speedup, while asynchronous approaches suffer from accuracy degradation due to a different scheme from a single worker. In this paper, we propose AshPipe, a hybrid parallel framework that combines data parallelism and asynchronous pipeline parallelism to achieve efficient speedup for training. The proposed runtime uses the 1F1B schedule and data parallelism, with non-uniform numbers of workers and identical global batch sizes across stages. A Switch parallelism (SP) mechanism is also proposed as an option to mitigate accuracy degradation, which switches over from data parallelism to hybrid parallelism in the course of training. Experimental results show that AshPipe achieves 1.844x the throughput of data parallelism for ViT-H/14 whose parameter size is 632M. With the SP mechanism, AshPipe achieved a 30.2% reduction in training time with comparable accuracy compared to data parallelism when training on the CIFAR100 dataset.

关键词： distributed Deep Learning Data parallelism Pipeline parallelism Hybrid parallelism

来源：评论

学校读者我要写书评

暂无评论

Traceable Ring Signature Scheme in Internet of Vehicles Based on Lattice Cryptography 21

Traceable Ring Signature Scheme in Internet of Vehicles Base...

引用

作者： Liao, Wei Han, Lansheng Chen, Peng Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350329223

Lattice cryptography, as a recognized Cryptosystem that can resist quantum computation, has great potential for development. Lattice based signature scheme is currently a research focus. In this paper, the traceable ring signature scheme based on lattice cryptography in the Internet of Vehicles (IoV) environment is studied. Firstly, users' public and private keys are generated on the lattice, which effectively reduces the key size and time cost. Secondly, the scheme also achieves traceability by adding additional information. The scheme satisfies strong unforgeability, traceability, and anonymity. In addition, the traceable ring signature scheme based on lattice cryptography is applied in the IoV environment to effectively protect user privacy. Model communication can not only protect user privacy, but also trace the signer when necessary, achieving a balance between security and privacy. The simulation results show that the average delay of IoV of our scheme is better than that of similar schemes. The research in this paper improves the security of data transmission in the IoV environment, enables it to adapt to the complex and changeable new network environment, and effectively guarantees the information security of vehicles and owners. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

CMS: A Computility Resource Status Management and Storage Framework 20th

CMS: A Computility Resource Status Management and Storage F...

引用

20th IFIP WG 10.3 international conference on Network and parallel computing, NPC 2024

作者： Peng, Xiaohui Luo, Xudong Chang, Kuo Wang, Yifan Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Nanjing Institute of InforSuperBahn Nanjing China

ISBN: (纸本)9789819628292

With the increasing demand for computility, managing distributed computility resources is crucial for improving service quality and performance of the cross-region computility infrastructure. In order to ensure timely and accurate scheduling of computing tasks on such infrastructure, a distributed computility status storage and query system is needed to achieve millisecond-level performance in terms of multidimensional sort query and multidimensional range query for computility status. Thus, we propose CMS, a computility resource status management and storage framework, which leverages specialized multidimensional indexes to support millisecond-level resource status reporting and querying, as well as sort and range queries. In addition, we developed BCQL and a set of querying algorithms to enhance throughput and reduce query latency. Experimental results show that the average query latency of the multidimensional sorting queries and range queries of the CMS system is 2.499 ms and 2.014 ms, respectively. While, the latency of those queries in Redis-based framework reach 25.66 ms and 25.13 ms, which are 10× higher than the CMS. © IFIP international Federation for Information Processing 2025.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

distributed and parallel Low-Diameter Decompositions for Arbitrary and Restricted Graphs 16

Distributed and Parallel Low-Diameter Decompositions for Arb...

引用

16th Innovations in Theoretical Computer Science conference, ITCS 2025

作者： Dou, Jinfeng Götte, Thorsten Hillebrandt, Henning Scheideler, Christian Werthmann, Julian Paderborn University Germany University of Hamburg Germany

ISBN: (纸本)9783959773614

We consider the distributed and parallel construction of low-diameter decompositions with strong diameter. We present algorithms for arbitrary undirected, weighted graphs and also for undirected, weighted graphs that can be separated through k ∈ Õ(1) shortest paths. This class of graphs includes planar graphs, graphs of bounded treewidth, and graphs that exclude a fixed minor Kr. Our algorithms work in the PRAM, CONGEST, and the novel HYBRID communication model and are competitive in all relevant parameters. Given D > 0, our low-diameter decomposition algorithm divides the graph into connected clusters of strong diameter D. For an arbitrary graph, an edge e ∈ E of length e is cut between two clusters with probability O(e·log(n)D). If the graph can be separated by k ∈ Õ(1) paths, the probability improves to O(e·log log nD). In either case, the decompositions can be computed in Õ(1)1 depth and Õ(m) work in the PRAM and Õ(1) time in the HYBRID model. In CONGEST, the runtimes are Õ(HD + √n) and Õ(HD) respectively. All these results hold w.h.p.2 Broadly speaking, we present distributed and parallel implementations of sequential divide-and-conquer algorithms where we replace exact shortest paths with approximate shortest paths. In contrast to exact paths, these can be efficiently computed in the distributed and parallel setting [STOC’22]. Further, and perhaps more importantly, we show that instead of explicitly computing vertex-separators to enable efficient parallelization of these algorithms, it suffices to sample a few random paths of bounded length and the nodes close to them. Thereby, we do not require complex embeddings whose implementation is unknown in the distributed and parallel setting. © Jinfeng Dou, Thorsten Götte, Henning Hillebrandt, Christian Scheideler, and Julian Werthmann.

关键词： Undirected graphs

来源：评论

学校读者我要写书评

暂无评论

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability 24

ORBIT: Oak Ridge Base Foundation Model for Earth System Pred...

引用

2024 international conference for High Performance computing, Networking, Storage and Analysis

作者： Wang, Xiao Liu, Siyan Tsaris, Aristeidis Choi, Jong-Youl Aji, Ashwin M. Fan, Ming Zhang, Wei Yin, Junqi Ashfaq, Moetasim Lu, Dan Balaprakash, Prasanna Oak Ridge Natl Lab Oak Ridge TN 37830 USA AMD Res & Adv Dev Santa Clara CA 95054 USA

ISBN: (数字)9798350352917

ISBN: (纸本)9798350352924;9798350352917

Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by leveraging large and heterogeneous data, are often constrained by their size and data integration, limiting their effectiveness in addressing the full range of Earth system prediction challenges. To overcome these limitations, we introduce the Oak Ridge Base Foundation Model for Earth System Predictability (ORBIT), an advanced vision transformer model that scales up to 113 billion parameters using a novel hybrid tensor-data orthogonal parallelism technique. As the largest model of its kind, ORBIT surpasses the current climate AI foundation model size by a thousandfold. Performance scaling tests conducted on the Frontier supercomputer have demonstrated that ORBIT achieves 684 petaFLOPS to 1.6 exaFLOPS sustained throughput, with scaling efficiency maintained at 41% to 85% across 49,152 AMD GPUs. These breakthroughs establish new advances in AI-driven climate modeling and demonstrate promise to significantly improve the Earth system predictability.

关键词： Earth Limiting Foundation models Predictive models parallel processing Transformers Throughput Supercomputers Planetary orbits Meteorology

来源：评论

学校读者我要写书评

暂无评论

A Latency Guaranteed Scheduling Strategy under Performance Constraints in Big Data Stream computing Environments 29

A Latency Guaranteed Scheduling Strategy under Performance C...

引用

29th IEEE international conference on parallel and distributed Systems, ICPADS 2023

作者： Sun, Dawei Guan, Chengjun Fan, Yinuo Rung, Jia Gao, Shang China University of Geosciences School of Information Engineering Beijing100083 China Monash University Department OfData Science and Al ClaytonVIC3800 Australia DeakinUniversity School of Information Technology Waum PondsVIC3216 Australia

ISBN: (纸本)9798350330717

Efficient utilization of computing resources in a stream computing environment is crucial for system performance. Existing scheduling strategies can hardly guarantee latency under performance constraints, let alone accounting for the communication cost incurred by scheduling itself. To address these issues, we propose Lg-Stream, a latency guaranteed scheduling strategy under performance constraints. This paper discusses the Lg-Stream strategy from the following aspects: (1) We model the topology as a queuing network to evaluate the system latency;(2) For scenarios with limited resources and latency constraints, we ensure that each executor-to-component allocation optimizes the system's processing latency to the maximum, consequently altering the components' parallelism;(3) We place executors that communicate with each other on the same node as much as possible. Experimental results demonstrated that in comparison to existing state-of-the-art scheduling strategies, it reduces the average system latency up to 30%. © 2023 IEEE.

关键词： Big data parallelism Resource scheduling Storm Stream processing

来源：评论

学校读者我要写书评

暂无评论

Protection of Express Information Using parallel computing 4

Protection of Express Information Using Parallel Computing

引用

4th international conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Zhang, Fangfang Liaoning Economy Vocational and Technical College Shenyang110122 China

ISBN: (纸本)9798350337181

In daily life, our express information items are stored in the server of express company. To avoid the leakage of the users' private information, this paper proposes a fast encryption algorithm to protect them. The proposed method first creates multiple threads. Then the information items are grouped into multiple groups with the same number of threads. Next, each thread employs a chaos-based encryption algorithm to encrypt the express information. Finally, the proposed method output the ciphered express information. Security analysis and efficiency test are carried out, and the results show that the proposed method can resist brute-force attack, statistical analysis, and have high efficiency compared with serial encryption mode. © 2023 IEEE.

关键词： Cryptography

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500页 << < 51 52 53 54 55 56 57 58 59 60 > >>

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：