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

6,707 篇 会议
116 册 图书
72 篇 期刊文献

馆藏范围

6,895 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,563 篇 工学
- 3,369 篇 计算机科学与技术...
- 1,739 篇 软件工程
- 1,054 篇 信息与通信工程
- 675 篇 电气工程
- 229 篇 控制科学与工程
- 179 篇 电子科学与技术（可...
- 143 篇 机械工程
- 97 篇 动力工程及工程热...
- 97 篇 生物工程
- 94 篇 测绘科学与技术
- 42 篇 生物医学工程（可授...
- 40 篇 仪器科学与技术
- 39 篇 光学工程
- 34 篇 建筑学
- 29 篇 土木工程
- 28 篇 安全科学与工程
- 28 篇 网络空间安全
771 篇 理学
- 568 篇 数学
- 112 篇 生物学
- 102 篇 统计学（可授理学、...
- 100 篇 物理学
- 75 篇 系统科学
- 37 篇 化学
512 篇 管理学
- 384 篇 管理科学与工程(可...
- 197 篇 工商管理
- 155 篇 图书情报与档案管...
82 篇 医学
- 80 篇 临床医学
- 25 篇 基础医学(可授医学...
42 篇 经济学
- 42 篇 应用经济学
35 篇 法学
- 25 篇 社会学
12 篇 农学
10 篇 文学
8 篇 教育学
8 篇 军事学
1 篇 艺术学

主题

899 篇 distributed comp...
802 篇 computer network...
513 篇 concurrent compu...
450 篇 wireless sensor ...
377 篇 parallel process...
354 篇 computer science
352 篇 routing
344 篇 neural networks
342 篇 computational mo...
304 篇 computer archite...
260 篇 application soft...
255 篇 network topology
253 篇 peer to peer com...
253 篇 protocols
244 篇 bandwidth
235 篇 grid computing
232 篇 software enginee...
189 篇 costs
177 篇 intelligent netw...
176 篇 artificial intel...

机构

28 篇 institute of com...
24 篇 shandong provinc...
20 篇 key laboratory o...
15 篇 shandong fundame...
14 篇 department of co...
13 篇 university of ch...
12 篇 department of co...
11 篇 department of co...
11 篇 department of co...
11 篇 institute of com...
11 篇 national laborat...
11 篇 beijing universi...
10 篇 college of compu...
10 篇 institute of inf...
10 篇 school of cyber ...
10 篇 department of co...
10 篇 school of comput...
9 篇 shandong enginee...
9 篇 department of co...
9 篇 school of comput...

作者

15 篇 m. takizawa
15 篇 li dongsheng
15 篇 shen hong
15 篇 hong shen
15 篇 jiannong cao
14 篇 shietung peng
14 篇 eyas el-qawasmeh
13 篇 lemin li
13 篇 rothermel kurt
12 篇 hai jin
11 篇 dongsheng li
11 篇 wei zhang
10 篇 koibuchi michihi...
10 篇 jack dongarra
10 篇 t. enokido
10 篇 wang yang
10 篇 stephen l. scott
10 篇 j. duato
10 篇 m. ould-khaoua
9 篇 duerr frank

语言

6,687 篇 英文
196 篇 其他
17 篇 中文

检索条件"任意字段=IASTED International Conference on Parallel and Distributed Computing and Networks"

共 6895 条记录，以下是561-570 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：

Enhancing the Scalability of Knowledge Discovery Services for Massive Data Mining on Clouds

Enhancing the Scalability of Knowledge Discovery Services fo...

引用

IoT Based Control networks and Intelligent Systems (ICICNIS), international conference on

作者： Vijayakumar Sajjan Jayam Pradeep Kumar Vikram Kalvala Narsaiah Domala B. Kiran Kumar C P Pavan Kumar Hota Department Of CSE Malla Reddy University Hyderabad Department Of ECE Chaitanya Deemed to be University Hyderabad Department Of ECE MLR Institute Of Technology Hyderabad Department Of Artificial Intelligence Shri Vishnu Engineering College for Women Bhimavaram

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

The traditional data mining techniques do not work well when it comes to the big data and the tremendous growth rate of the digital data also becomes a major challenge to the discovery of knowledge. Cloud computing offers an ideal solution to computationally and storage intensive tasks with scalable and on-demand services that can process big data at short notice. This paper reviews the current models that employ cloud structure for distributed data mining as well as models like CosDic and the Data Mining Cloud Framework (DMCF). The way of processing large datasets is also represented well by the Map Reduce model where it is possible to implement the data processing in parallel on several nodes. Despite the fact that cloud-based systems are very useful when it comes to the management of large amounts of data, challenges such as privacy, data security and data coordination still persist. These innovative methodologies include Edge computing and Federated Learning that are anticipated to solve the mentioned issues by enhancing the speed of data processing and its safety. Thus, scalable cloud data mining to meet growing needs of knowledge discovery in big data contexts will have to develop new privacy protection mechanisms, integration of cloud models, and complex algorithms.

关键词： Cloud computing Federated learning Reviews Scalability Computational modeling Big Data Knowledge discovery Data processing Data models Edge computing

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-empowered Network Measurement: A Critical Path to Traffic Anomaly Detection in IoT-enabled Smart Grid

Machine Learning-empowered Network Measurement: A Critical P...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Hongrui Zang Hongbo Liu Wei Sun Guangyuan Zhang Xiangyu Kong State Grid Jilin Electric Power Company Limited Communication Company Branch Changchun China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Large-scale deployment of Internet of Things (IoT) devices provides efficient data collection and control capabilities in the smart grid, while edge computing plays a key role in increasing the speed of data processing and reducing latency. The growth of edge computing in the smart grid is inevitably increasing the stability requirement in network transmission and the necessity of adequate network measurement to detect traffic anomalies. There are two challenges for measurement in IoT-enabled networks. The first challenge is the high processing speed and limited memory space. The second challenge is the varying network traffic. This paper studies how to use sketch techniques to fulfill the required capabilities of network measurement. Sketches have been considered as the most promising solution for network measurement in recent years, because they greatly optimize the speed and memory usage at the cost of small error. However, most sketches do not work well for varying network traffic. These sketches require to adjust their internal memory usage while the optimal point is sensitive to specified flow size distribution and memory size. To address this problem, we propose a machine learning empowered sketch framework. The proposed sketch framework trains a neural network model that online adjusts the memory usage based on a small sample of flow. We conduct data-driven simulations to evaluate the proposed framework. By comparing measurement results on public dataset, we can see that the proposed framework significantly improves the accuracy of measurement and anomaly detection without sacrificing the line-rate processing capability.

关键词： Accuracy Power measurement Memory management Estimation Telecommunication traffic Smart grids Resource management Internet of Things Anomaly detection Edge computing

来源：评论

学校读者我要写书评

暂无评论

CAPTURE: Memory-Centric Partitioning for distributed DNN Training with Hybrid parallelism

CAPTURE: Memory-Centric Partitioning for Distributed DNN Tra...

引用

international conference on High Performance computing

作者： Henk Dreuning Kees Verstoep Henri E. Bal Rob V. van Nieuwpoort University of Amsterdam Amsterdam The Netherlands Vrije Universiteit Amsterdam Amsterdam The Netherlands Leiden University Leiden The Netherlands

Deep Learning (DL) model sizes are increasing at a rapid pace, as larger models typically offer better statistical performance. Modern Large Language Models (LLMs) and image processing models contain billions of trainable parameters. Training such massive neural networks incurs significant memory requirements and financial cost. Hybrid-parallel training approaches have emerged that combine pipelining with data and tensor parallelism to facilitate the training of large DL models on distributed hardware setups. However, existing approaches to design a hybrid-parallel partitioning and parallelization plan for DL models focus on achieving high throughput and not on minimizing memory usage and financial cost. We introduce CAPTURE, a partitioning and parallelization approach for hybrid parallelism that minimizes peak memory usage. CAPTURE combines a profiling-based approach with statistical modeling to recommend a partitioning and parallelization plan that minimizes the peak memory usage across all the Graphics Processing Units (GPUs) in the hardware setup. Our results show a reduction in memory usage of up to 43.9% compared to partitioners in state-of-the-art hybrid-parallel training systems. The reduced memory footprint enables the training of larger DL models on the same hardware resources and training with larger batch sizes. CAPTURE can also train a given model on a smaller hardware setup than other approaches, reducing the financial cost of training massive DL models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Edge Assistance for Solving Matrix Eigenvalue Problem

Privacy-Preserving Edge Assistance for Solving Matrix Eigenv...

引用

international conference on Computer Communications and networks (ICCCN)

作者： Xiaotong Zhao Hanlin Zhang Jie Lin Fanyu Kong Leyun Yu College of Computer Science and Technology Qingdao University Qingdao China School of Computer Science and Technology Xian Jiaotong University Xian China School of Computer Science and Technology Shandong University Jinan China JIC IOT CO. LTD Nanchang China

ISBN: (数字)9798350384611

ISBN: (纸本)9798350348439

The large-scale matrix eigenvalue computation, as a basic mathematical tool, has been widely used in many fields such as face recognition and data analysis. However, local terminal devices lack sufficient resources to undertake heavy computational tasks, which poses a challenge to the applications of eigenvalue computation. In this paper, we propose the first privacy-preserving edge-assisted computation scheme for solving the largest eigenvalue and corresponding eigenvector. We propose a privacy-preserving transformation method to protect data privacy and prevent edge servers from retrieving sensitive information. Mean-while, we design a verification scheme to ensure the correctness of the results returned by the edge servers. In addition, we design a distributed parallel computing scheme to ensure the efficiency of edge computation. Through theoretical analysis and simulation experiments, we verify the feasibility and efficiency of our proposed scheme.

关键词： Performance evaluation Data privacy Protocols Face recognition parallel processing Eigenvalues and eigenfunctions Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

27th international European conference on parallel and distributed computing, Euro-Par 2021

27th International European Conference on Parallel and Distr...

引用

27th international European conference on parallel and distributed computing, Euro-Par 2021

ISBN: (纸本)9783030856649

The proceedings contain 38 papers. The special focus in this conference is on parallel and distributed computing. The topics include: An MPI-based Algorithm for Mapping Complex networks onto Hierarchical Architectures;pipelined Model parallelism: Complexity Results and Memory Considerations;efficient and Systematic Partitioning of Large and Deep Neural networks for parallelization;A GPU Architecture Aware Fine-Grain Pruning Technique for Deep Neural networks;Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs;smart distributed DataSets for Stream Processing;colony: parallel Functions as a Service on the Cloud-Edge Continuum;horizontal Scaling in Cloud Using Contextual Bandits;geo-distribute Cloud Applications at the Edge;Automatic Low-Overhead Load-Imbalance Detection in MPI Applications;A Fault Tolerant and Deadline Constrained Sequence Alignment Application on Cloud-Based Spot GPU Instances;sustaining Performance While Reducing Energy Consumption: A Control Theory Approach;algorithm Design for Tensor Units;a Scalable Approximation Algorithm for Weighted Longest Common Subsequence;TSLQueue: An Efficient Lock-Free Design for Priority Queues;G-Morph: Induced Subgraph Isomorphism Search of Labeled Graphs on a GPU;accelerating Graph Applications Using Phased Transactional Memory;Efficient GPU Computation Using Task Graph parallelism;towards High Performance Resilience Using Performance Portable Abstractions;Enhancing Load-Balancing of MPI Applications with Workshare;trace-Based Workload Generation and Execution;particle-In-Cell Simulation Using Asynchronous Tasking;Exploiting Co-execution with OneAPI: Heterogeneity from a Modern Perspective;designing a 3D parallel Memory-Aware Lattice Boltzmann Algorithm on Manycore Systems;Fault-Tolerant LU Factorization Is Low Cost;Mixed Precision Incomplete and Factorized Sparse Approximate Inverse Preconditioning on GPUs;GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

dBFC: Destination-based Backpressure Flow Control for Incast

dBFC: Destination-based Backpressure Flow Control for Incast

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Zewei Guan Wenxin Li Xin He Song Zhang Keqiu Li College of Intelligence and Computing Tianjin University China

Incast happens in data center networks (DCNs) when many senders simultaneously send flows to one receiver. Incast occurs frequently and compromises flow performance severely. However, widely deployed end-to-end congestion control (CC) protocols are inefficient at handling incast, as they rely on delayed congestion signals and can not isolate incast flows. Recently, researchers have favored per-hop flow control protocols since they could achieve fast reaction and incast isolation. Nevertheless, these impressive advantages are impractical because of hardware resource *** this paper, we present a new per-hop flow control protocol dBFC (Destination-based Backpressure Flow Control), which achieves these advantages within limited hardware resources. Our key insight is that the number of destinations reached by queued packets in a port is minuscule. dBFC is compatible with existing CC protocols. We use large-scale NS3 simulations to evaluate dBFC. In our evaluation, compared with deployed CC protocols and the state-of-the-art per-hop flow control protocol, dBFC reduces the maximum buffer occupancy by 5 − 23× and thus provides up to 21× lower flow completion time of small flows in limited hardware resources.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploring the Impact of Serverless computing on Peer To Peer Training Machine Learning

Exploring the Impact of Serverless Computing on Peer To Peer...

引用

IEEE international conference on Cloud Engineering (IC2E)

作者： Amine Barrak Ranim Trabelsi Fehmi Jaafar Fabio Petrillo Department of Computer Science and Mathematics University of Quebec at Chicoutimi UQAC Saguenay Canada Département de génie Logiciel École de Technologie Supérieure ÉTS Montreal

The increasing demand for computational power in big data and machine learning has driven the development of distributed training methodologies. Among these, peer-to-peer (P2P) networks provide advantages such as enhanced scalability and fault tolerance. However, they also encounter challenges related to resource consumption, costs, and communication overhead as the number of participating peers grows. In this paper, we introduce a novel architecture that combines serverless computing with P2P networks for distributed training and present a method for efficient parallel gradient computation under resource *** findings show a significant enhancement in gradient computation time, with up to a 97.34% improvement compared to conventional P2P distributed training methods. As for costs, our examination confirmed that the serverless architecture could incur higher expenses, reaching up to 5.4 times more than instance-based architectures. It is essential to consider that these higher costs are associated with marked improvements in computation time, particularly under resource-constrained *** the cost-time trade-off, the serverless approach still holds promise due to its pay-as-you-go model. Utilizing dynamic resource allocation, it enables faster training times and optimized resource utilization, making it a promising candidate for a wide range of machine learning applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

GA-Net: Gated Attention Mechanism Based Global Refinement Network for Image Inpainting

GA-Net: Gated Attention Mechanism Based Global Refinement Ne...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Ran Qiu Shengrong Zhao Hu Liang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

Underwater images are often affected by problems such as light attenuation, color distortion, noise and scattering, resulting in image defects. A novel image inpainting method is proposed to intelligently predict and fill damaged areas for complete and continuous visualization of the image. First, in order to effectively solve the problem of color distortion caused by light refraction in underwater environments, the improved gated attention mechanism is used. This mechanism improves the local details by learning and weighting the important features of the image. Second, gated convolution automatically determines the degree of restoration for each pixel based on local features of the original image. It eliminates distractions such as low contrast and scattering, retaining more original detailed information. By doing so, image inpainting techniques improve the quality and visualization of underwater images.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Communication-aware Quantization for Deep Learning Inference parallelization on Chiplet-based Accelerators

Communication-aware Quantization for Deep Learning Inference...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Kaiwei Zou Songyun Qu Wen Li Ying Wang Huawei Li Yongpan Liu Tsinghua University Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer and Information Technology Shanxi University Taiyuan China

It has recently become trendy for neural network accelerators to scale from single-core to chiplet-based multichip architecture, as the growth of neural network depth and complexity are calling for the promotion of computation and memory capabilities. However, the unintended extensive inter-chip communication of chiplet-based accelerator may bottleneck the parallelism of deep learning inference, which is undesirable for many real-time applications and energy-efficient devices. Although it is imperative for novel schemes to be devised to alleviate this problem, related works are scarce. In this work, we present CampQ, a fine-grained communication-aware mixed-precision quantization method to accelerate inference parallelization by reducing the major inter-chiplet communication overhead. By leveraging the AutoML technique, CampQ is capable of determining different bit-width to activation groups according to thier transmission distances in on-package network. The experimental results show 1.4×-2.6× performance benefits and 29%-60% energy reduction over the 16-bit models for various neural networks and parallelism approaches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Scalability in Blockchain networks: An Improved Sharding Protocol Using Verifiable Random Function (VRF) for Shard Assignment

Enhancing Scalability in Blockchain Networks: An Improved Sh...

引用

international conference on parallel distributed and Grid computing (PDGC)

作者： Rajesh Sharma R Akey Sungheetha Mohit Tiwari Rajiv Gandhi K GS Pradeep Ghantasala Ellappan. V Department of Computer Science and Engineering Alliance University Bengaluru India Department of Computer Science and Engineering Bharthi Vidyapeeth’s College of Engineering Delhi Government Arts and Science College for Women India Department of Computer Science and Engineering Alliance University Bangalore India Department of ECE Mahendra Institute of Technology Namakkal Tamil Nadu

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

The use of blockchain is, however, faced with scalability issues which is a major hindrance to adoption. Sharding has proven to be an effective solution among the proposed ones though the existing ones are hindered with the problems of security and efficiency. In this paper, to enhance the proposed sharding protocol, we incorporate Verifiable Random Functions (VRF) for the distribution of shards. The given protocol includes the usage of VRF algorithm with dynamic reshuffle method which is comparatively newer and proven to enhance both security as well as load balance. It showed that simulations had improved the process of transaction throughput by 40% in relation to current shard protocols. The proposed method achieved 99.7%. permissions of the true values while the misclassification rate was compared with other relevant works which was lower than the proposed method. the shard takeover attacks and have cut down the cross-shard communication to 35%. Thus, it has been observed that load balancing efficiency of these shards have improved by 28 % in general. The sharding protocol proposed in this paper based on VRF provides blockchain with high scalability and strong security. The approach is suitable for scaling of Blockchains for Big Applications which includes BFSI and Supply chain solutions.

关键词： Sharding Protocols Scalability Heuristic algorithms Supply chains Load management Throughput Blockchains Security Load modeling

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 << < 53 54 55 56 57 58 59 60 61 62 > >>

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：