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

33,159 篇 会议
831 篇 期刊文献
231 册 图书
1 篇 学位论文
1 篇 科技报告

馆藏范围

34,223 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

20,136 篇 工学
- 17,854 篇 计算机科学与技术...
- 7,807 篇 软件工程
- 4,543 篇 电气工程
- 2,839 篇 信息与通信工程
- 1,459 篇 控制科学与工程
- 745 篇 电子科学与技术（可...
- 685 篇 动力工程及工程热...
- 468 篇 机械工程
- 381 篇 生物工程
- 339 篇 石油与天然气工程
- 302 篇 仪器科学与技术
- 248 篇 生物医学工程（可授...
- 247 篇 环境科学与工程（可...
- 247 篇 网络空间安全
- 217 篇 力学（可授工学、理...
- 205 篇 建筑学
- 192 篇 材料科学与工程（可...
- 190 篇 安全科学与工程
- 185 篇 土木工程
4,376 篇 理学
- 2,838 篇 数学
- 884 篇 物理学
- 531 篇 系统科学
- 471 篇 生物学
- 424 篇 统计学（可授理学、...
- 229 篇 化学
3,202 篇 管理学
- 2,473 篇 管理科学与工程(可...
- 1,262 篇 工商管理
- 964 篇 图书情报与档案管...
287 篇 经济学
- 281 篇 应用经济学
287 篇 医学
- 217 篇 临床医学
191 篇 法学
98 篇 农学
97 篇 教育学
77 篇 文学
10 篇 艺术学
9 篇 军事学
1 篇 哲学

主题

4,289 篇 grid computing
4,219 篇 distributed comp...
2,063 篇 concurrent compu...
2,043 篇 cloud computing
2,017 篇 parallel process...
1,844 篇 computational mo...
1,619 篇 computer archite...
1,403 篇 computer science
1,362 篇 application soft...
1,288 篇 resource managem...
1,257 篇 computer network...
988 篇 processor schedu...
782 篇 scalability
777 篇 distributed comp...
765 篇 high performance...
760 篇 peer to peer com...
682 篇 costs
670 篇 distributed data...
666 篇 algorithm design...
651 篇 middleware

机构

52 篇 department of co...
47 篇 school of comput...
46 篇 institute of com...
45 篇 college of compu...
39 篇 huazhong univ sc...
34 篇 china electric p...
34 篇 shanghai jiao to...
33 篇 school of comput...
32 篇 school of comput...
31 篇 univ chinese aca...
31 篇 department of co...
27 篇 inria
27 篇 tsinghua univ de...
27 篇 university of ch...
25 篇 shandong provinc...
24 篇 tsinghua univers...
23 篇 huazhong univers...
23 篇 institute of par...
23 篇 nanjing univ sta...
23 篇 college of intel...

作者

69 篇 jin hai
51 篇 hai jin
49 篇 rajkumar buyya
39 篇 fahringer thomas
37 篇 zomaya albert y.
33 篇 liu yang
31 篇 li dongsheng
29 篇 dongsheng li
29 篇 m. takizawa
27 篇 duerr frank
26 篇 li li
24 篇 xhafa fatos
23 篇 wei li
22 篇 wang lei
22 篇 yang yang
20 篇 lei wang
20 篇 xuejun yang
19 篇 dongarra jack
18 篇 singh bhim
18 篇 bala piotr

语言

33,794 篇 英文
250 篇 其他
143 篇 中文
43 篇 俄文
2 篇 乌克兰文
1 篇 德文
1 篇 西班牙文
1 篇 法文
1 篇 葡萄牙文
1 篇 土耳其文

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

共 34223 条记录，以下是4691-4700 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：

Heuristic Allocation Strategies for Dependable Scheduling in Heterogeneous computing Environments 15th

Heuristic Allocation Strategies for Dependable Scheduling in...

引用

15th international conference on Dependability of Computer Systems (DepCoS-RELCOMEX)

作者： Toporkov, Victor Yemelyanov, Dmitry Natl Res Univ MPEI Ul Krasnokazarmennaya 14 Moscow 111250 Russia

ISBN: (纸本)9783030482558;9783030482565

In this work, we consider heuristic resources allocation strategies for parallel jobs execution in heterogeneous computing environments. Existing modern job-flow execution features and realities impose many restrictions for the resources allocation procedures and applicable scheduling criteria. Subject to these restrictions a special dynamic programming scheme is proposed to select resources depending on their meta-features. When applied to secondary scheduling criteria this procedure may be used to generate job flow scheduling strategies while maintaining the same primary scheduling criterion outcomes. Such secondary criteria optimization is commonly referred as breaking a tie rules. Based on a conservative backfilling scheduling procedure we study how different breaking a tie heuristics affect integral job-flow scheduling characteristics in a dedicated simulation environment.

关键词： distributed computing grid Coordination Resources allocation Slot Job Backfilling Breaking a tie rules

来源：评论

学校读者我要写书评

暂无评论

Optimization of key and value storage in vector map rendering

Optimization of key and value storage in vector map renderin...

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Feng Jing Ying Jiang Shengbin Chen Xirong Lv Jiayi He State Grid Shanxi Electric Power Company Taiyuan China Xiamen Great Power Geo Information Technology Company Ltd Xiamen China School of Computer and Information Engineering Xiamen University of Technology Xiamen China

With the continuous development of data-centric Internet applications, data management solutions for massive data have gradually become a new research direction in vector map rendering. The introduction of distributed "cloud computing" technology has continuously improved the storage and management of massive data. Supported by a large number of distributed systems, it provides normal services to the outside world, as well as fast data location services. The system has good performance in data storage efficiency, node load balancing and system scalability, and has an efficient data positioning mechanism. The basic idea of the system design draws on the hash algorithm and the consistent hash algorithm, and improves the scalability of the basic algorithm. Through the three-tier layout: front-end server layer, consistent hash layer, data node layer, to maximize the consistency, availability, efficiency and scalability of the system.

关键词： Cloud computing Scalability Layout Memory distributed databases Systems architecture Rendering (computer graphics)

来源：评论

学校读者我要写书评

暂无评论

Context-aware Community Evolution Prediction in Online Social Networks

Context-aware Community Evolution Prediction in Online Socia...

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Alexander Lercher Nishant Saurabh Radu Prodan Institute of Information Technology University of Klagenfurt Austria Department of Information and Computing Sciences Utrecht University Netherlands

Community evolution prediction enables business-driven social networks to detect customer groups modeled as communities based on similar interests by splitting them into temporal segments and utilizing ML classification to predict their structural changes. Unfortunately, existing methods overlook business contexts and focus on analyzing customer activities, raising privacy concerns. This paper proposes a novel method for community evolution prediction that applies a context-aware approach to identify future changes in community structures through three complementary features. Firstly, it models business events as transactions, splits them into explicit contexts, and detects contextualized communities for multiple time windows. Secondly, it uses novel structural metrics representing temporal features of contextualized communities. Thirdly, it uses extracted features to train ML classifiers and predict the community evolution in the same context and other dependent contexts. Experimental results on two real-world data sets reveal that traditional ML classifiers using the context-aware approach can predict community evolution with up to three times higher accuracy, precision, recall, and F1-score than other baseline classification methods (i.e., majority class, persistence).

关键词： Measurement Privacy Social networking (online) Predictive models Feature extraction Context modeling Business

来源：评论

学校读者我要写书评

暂无评论

Adaptive Response Technology for Threats in Power IoT Terminals Based on Reinforcement Learning

Adaptive Response Technology for Threats in Power IoT Termin...

引用

Mechatronics, IoT and Industrial Informatics (ICMIII), international conference on

作者： Changhua Sun Xin Sun Yifeng Wang Hua Dai Futai Zou Mingyi Huang State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350386639

ISBN: (纸本)9798350386646

The power Internet of Things (IoT) terminal is an integral part of the power system and faces a complex network attack scenario. When the power system detects a network attack, it needs to generate disposal scripts to respond to the attack. Traditional network threat response technologies struggle to handle new types of network attacks, so introducing artificial intelligence algorithms to generate disposal scripts is necessary to enhance response success rates. However, power IoT terminals typically have limited computing resources and struggle to execute artificial intelligence algorithms. To address this issue, this paper proposes a power IoT threat response technology based on reinforcement learning, employing a client-server architecture. Here, the client represents the power IoT terminal requiring threat response, while the server functions as the threat disposal center within the power system. Upon receiving threat information, the threat disposal center initially processes it into the necessary response actions. Subsequently, it invokes the reinforcement learning algorithm to produce the operation sequence required by the client to respond and generates distinct disposal scripts tailored to the system environment of each power IoT terminal. These scripts are then distributed to the clients for response. After executing the disposal script, the clients compute the reinforcement learning reward value based on execution results and transmit it back to the server. The server adjusts the response action sequence based on the reward value received from the client and regenerates the disposal script. This iterative process continues until the client successfully completes the threat response. Experiments demonstrate that the power IoT threat response architecture proposed in this paper achieved a 100% response success rate in two threat response scenarios, conclusively showcasing its effectiveness in completing power IoT threat response tasks.

关键词： Mechatronics Reinforcement learning Computer architecture Malware Power systems Servers Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Hyperbolic Contrastive Learning with Second Order Sampling for Collaborative Filtering

Hyperbolic Contrastive Learning with Second Order Sampling f...

引用

IEEE international conference on Web Services (ICWS)

作者： Longchuan Tu Shunmei Meng Lianyong Qi Xiaolong Xu Xuyun Zhang School of Computer Science and Engineering Nanjing University of Science and Technology China State Key Lab. for Novel Software Technology Nanjing University China College of Computer Science and Technology China University of Petroleum(East China) China School of Computer and Software Nanjing University of Information Science and Technology China School of Computing Macquarie University Australia

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

Recently, hyperbolic spaces have proven beneficial for service recommendation due to their exponentially growing spatial properties conforming to power-law distributed user-item networks. Among them, the combination of hyperbolic space with graph convolution has achieved great success. However, hyperbolic convolutional models still perform multi-layer convolution in tangent space (Euclidean space), leading to the still inevitable problem of over-smoothing arising from multi-layer convolution. In addition, most of these models randomly draw negative samples from items that users have not interacted with, so that some of the samples obtained may not be well suited for model optimization. To tackle the above challenges, we propose a new Hyperbolic GCN model based on Contrastive Learning and Second-order Reachable sampling for collaborative filtering (HG-CLSR), which improve high quality of representations by exploring the distribution of users and items in hyperbolic space. Specifically, We first introduce a root alignment approach to encourage embeddings to align with the tangent space, thereby reducing distortions during the embedding mapping process in space. Then, we perform contrastive learning in hyperbolic space to motivate the spatial distribution of nodes to better fit the hyperbolic space. Moreover, we sample in the user’s second-order reachable item set, which ensures that the negative sample is more similar to the positive sample, so that the negative node can provide better information for guiding model optimization. Extensive experiments on three real-world datasets demonstrate that the HG-CLSR is significantly superior compared to existing hyperbolic models.

关键词： Degradation Graphical models Convolution Web services Collaborative filtering Design methodology Contrastive learning Distortion Optimization Distribution functions

来源：评论

学校读者我要写书评

暂无评论

Herring: Rethinking the Parameter Server at Scale for the Cloud

Herring: Rethinking the Parameter Server at Scale for the Cl...

引用

international conference on High Performance computing, Networking, Storage and Analysis (SC)

作者： Thangakrishnan, Indu Cavdar, Derya Karakus, Can Ghai, Piyush Selivonchyk, Yauheni Pruce, Cory Amazon Web Serv Seattle WA 98109 USA

ISBN: (纸本)9781728199986

Training large deep neural networks is timeconsuming and may take days or even weeks to complete. Although parameter-server-based approaches were initially popular in distributed training, scalability issues led the field to move towards all -reduce -based approaches. Recent developments in cloud networking technologies, however, such as the Elastic Fabric Adapter (EFA) and Scalable Reliable Datagram (SRD), motivate a re -thinking of the parameter-server approach to address its fundamental inefficiencies. To this end, we introduce a novel communication library, Herring, which is designed to alleviate the performance bottlenecks in parameter-server-based training. We show that gradient reduction with Herring is twice as fast as all -reduce -based methods. We further demonstrate that training deep learning models like BERTiarge using Herring outperforms all -reduce -based training, achieving 85% scaling efficiency on large clusters with up to 2048 MINA V100 GPUs without accuracy drop.

关键词： Deep Learning Data parallel Training Scalability distributed parallel computing

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient Dynamic Load Balancing using Self-Organized Criticality in grid computing

Energy Efficient Dynamic Load Balancing using Self-Organized...

引用

IEEE international conference on High Performance computing and Communications (HPCC)

作者： Vivek Kumar Chinmaya Kumar Swain Aryabartta Sahu Dept. of CSE IIT Guwahati India Dept. of CSE SRM University India

grid computing refers to a collection of compute resources from different geographic locations to achieve a common objective. It involves tremendous amounts of computational task which require reliable resource sharing across the grid for efficiently executing the tasks. Load disparity is a major issue in grid computing. So effectively and efficiently utilize the potentials of huge distributed resources, load balancing algorithms are of primary importance. In this paper, we proposed an elegant approach using Bak-Tang-Wiesenfeld sandpile model for dynamically load-balancing of tasks across the processing sites in an energy efficient manner. The proposed approach reduces redundant migrations between processing sites by transferring tasks in a breadth first manner. In this approach avalanche propagation condition is stricter and depends on the average load of two adjacent layers of neighbours and use of signalling mechanism rather than actual transfer of tasks during an avalanche, until a destination comes in equilibrium. We experimentally validated by a number of numerical experiments using Google traces. The results of the experiments show the effectiveness of the proposed approach which reduces the number of migrations and improves the energy efficiency without much increasing the total flowtime and degrading the load balancing aspects as compared to state-of-the-art approaches.

关键词： Heuristic algorithms Computational modeling Load management grid computing Energy efficiency Internet Resource management

来源：评论

学校读者我要写书评

暂无评论

Load Balancing Optimization for Transformer in distributed Environment

Load Balancing Optimization for Transformer in Distributed E...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Delu Ma Zhou Lei Shengbo Chen Peng Wang School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai China

ISBN: (纸本)9781665408790

In recent years, the demand for artificial intelligence applications has increased dramatically. Complex models can promote machine learning to achieve excellent results, but computing efficiency has gradually reached a bottleneck. Therefore, more researchers are exploring the improvement of the efficiency of intelligent computing systems. distributed machine learning can improve the efficiency of model training and inference, but problems such as communication delay and load imbalance between computing nodes still exist. In the multi-GPU distributed computing environment, this paper takes the vision field algorithm VIT (vision transformer) as the optimization object, which has the advantage of convenient parallel training, and proposes several related solutions. Firstly, the parameter server is used as the system logic architecture and in order to reduce the idleness of the computing devices during the training process, the device working status query mechanism is designed to realize load balancing. Secondly, combined with the pre-trained small VIT algorithm model, semi-asynchronous communication method is proposed to reduce the communication overhead of computing devices and accelerate global convergence. The results of this experiment carried out in the existing distributed environment has demonstrated that compared with the existing synchronization method, the computational efficiency has been improved well under the premise of slightly reducing the accuracy.

关键词： Training Computational modeling Machine learning Load management Transformers Servers distributed computing

来源：评论

学校读者我要写书评

暂无评论

Comparison of Various Algorithms for Scheduling Tasks in a Desktop grid System Using a ComBos Simulator 10th

Comparison of Various Algorithms for Scheduling Tasks in a D...

引用

10th international conference on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2020

作者： Kurochkin, Ilya Kondrashov, Nikolay Institute for Information Transmission Problems Russian Academy of Sciences Bolshoy Karetny Lane 19 build.1 Moscow127051 Russia National Research University Higher School of Economics Pokrovsky Boulevard 11 Moscow109028 Russia

ISBN: (纸本)9783030668945

A desktop grid system is one of the most common types of distributed systems. The distinctive features of a desktop grid system are the high heterogeneity and unreliability of computing nodes. Desktop grid systems deployed on the BOINC platform are considered. To simulate the functioning of the desktop grid, a modified ComBos simulator based on Simgrid is used. The ComBos simulator adds support for applications with a limited number of tasks, asynchronous execution of multiple applications and various computing resources. Data from existing voluntary distributed computing projects were used to simulate the functioning of the desktop grid. The paper deals with the modification of scheduling system for a desktop grid. Algorithms FS, FCFS, SRPT, and SWRPT were selected from existing heuristic algorithms for comparison. Two heuristic algorithms for scheduling MSF and MPSF tasks were proposed. A simulation of the desktop grid was performed based on data from existing voluntary distributed computing projects. The simulation took into account asynchronous execution of five different computing applications on several types of computing resources. A comparative analysis of the results of various scheduling algorithms in the desktop grid is carried out. Analysis of the results showed that the proposed MPSF algorithm shows the best results from the compared algorithms. The proposed heuristic scheduling algorithm can be applied to umbrella distributed computing projects and to desktop grid in general. © 2020, Springer Nature Switzerland AG.

关键词： Simulators

来源：评论

学校读者我要写书评

暂无评论

Jupiter: a networked computing architecture 21

Jupiter: a networked computing architecture

引用

Proceedings of the 14th IEEE/ACM international conference on Utility and Cloud computing Companion

作者： Pradipta Ghosh Quynh Nguyen Pranav K Sakulkar Jason A. Tran Aleksandra Knezevic Jiatong Wang Zhifeng Lin Bhaskar Krishnamachari Murali Annavaram Salman Avestimehr University of Southern California

ISBN: (纸本)9781450391634

Modern latency-sensitive applications such as real-time multi-camera video analytics require networked computing to meet the time constraints. We present Jupiter, an open-source networked computing system that inputs a Directed Acyclic Graph (DAG)-based computational task graph to efficiently distribute the tasks among a set of networked compute nodes and orchestrates the execution thereafter. This Kubernetes container-orchestration-based system includes a range of profilers: network profilers, resource profilers, and execution time profilers; to support both centralized and decentralized scheduling algorithms. While centralized scheduling algorithms with global knowledge have been popular among the grid/cloud computing community, we argue that a distributed scheduling approach is better suited for networked computing due to lower communication and computation overhead in the face of network dynamics. We propose a new class of distributed scheduling algorithms called WAVE and show that despite using more localized knowledge, the WAVE algorithm can match the performance of a well-known centralized scheduling algorithm called Heterogeneous Earliest Finish Time (HEFT). To this, we present a set of real-world experiments on two separate testbeds: (1) a worldwide network of 90 cloud computers across eight cities and (2) a cluster of 30 Raspberry pi nodes.

关键词： container orchestration directed acyclic graph (DAG) dispersed computing kubernetes

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 << < 466 467 468 469 470 471 472 473 474 475 > >>

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：