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

1,699 篇 会议
48 册 图书
25 篇 期刊文献

馆藏范围

1,772 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,366 篇 工学
- 1,236 篇 计算机科学与技术...
- 550 篇 软件工程
- 241 篇 信息与通信工程
- 219 篇 电气工程
- 74 篇 控制科学与工程
- 50 篇 电子科学与技术（可...
- 43 篇 生物工程
- 34 篇 机械工程
- 26 篇 动力工程及工程热...
- 22 篇 仪器科学与技术
- 21 篇 力学（可授工学、理...
- 20 篇 建筑学
- 19 篇 土木工程
- 18 篇 生物医学工程（可授...
- 15 篇 材料科学与工程（可...
- 15 篇 安全科学与工程
- 14 篇 化学工程与技术
- 13 篇 石油与天然气工程
329 篇 理学
- 227 篇 数学
- 55 篇 物理学
- 51 篇 生物学
- 29 篇 系统科学
- 28 篇 统计学（可授理学、...
- 20 篇 化学
213 篇 管理学
- 157 篇 管理科学与工程(可...
- 66 篇 图书情报与档案管...
- 49 篇 工商管理
71 篇 医学
- 62 篇 临床医学
15 篇 法学
- 13 篇 社会学
14 篇 经济学
- 14 篇 应用经济学
9 篇 文学
8 篇 教育学
6 篇 农学
1 篇 军事学

主题

109 篇 distributed comp...
79 篇 parallel process...
76 篇 distributed comp...
62 篇 cloud computing
51 篇 parallel computi...
44 篇 computational mo...
41 篇 parallel program...
39 篇 computer archite...
35 篇 distributed data...
34 篇 fault tolerance
29 篇 concurrent compu...
29 篇 middleware
28 篇 parallel algorit...
28 篇 mapreduce
28 篇 parallel process...
26 篇 resource managem...
25 篇 application soft...
25 篇 big data
24 篇 wireless sensor ...
24 篇 protocols

机构

14 篇 saint petersburg...
7 篇 chinese acad sci...
6 篇 univ adelaide sc...
6 篇 institute of com...
5 篇 zhejiang univ co...
5 篇 shanghai jiao to...
5 篇 plekhanov russia...
4 篇 saint petersburg...
4 篇 harbin inst tech...
4 篇 meshcheryakov la...
4 篇 centre for distr...
4 篇 univ otago dept ...
4 篇 univ stuttgart i...
4 篇 st petersburg st...
4 篇 science and tech...
3 篇 huazhong univ sc...
3 篇 joint institute ...
3 篇 king saud univer...
3 篇 department of co...
3 篇 university of el...

作者

17 篇 zomaya albert y.
11 篇 shen hong
10 篇 bogdanov alexand...
9 篇 korkhov vladimir
8 篇 degtyarev alexan...
8 篇 albert y. zomaya
6 篇 li y
6 篇 taheri javid
5 篇 dustdar schahram
5 篇 leymann frank
5 篇 kopp oliver
5 篇 li kuan-ching
5 篇 kutovskiy nikola...
5 篇 nakayama shigeru
5 篇 huang z.
5 篇 sousa leonel
5 篇 gankevich ivan
5 篇 rothermel kurt
4 篇 jerzy waśniewski
4 篇 leung k.

语言

1,731 篇 英文
18 篇 中文
15 篇 其他
9 篇 俄文

检索条件"任意字段=9th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1772 条记录，以下是631-640 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：

Keynote Speech 6: China's New Key Project on High-Performance computing

Keynote Speech 6: China's New Key Project on High-Performanc...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Depei Qian Beihang University Beijing CN

ISBN: (纸本)9781509050826

Summary form only given. After a brief review on the current status of HPC research and development in China, this talk will introduce the plan of HPC development under the new Key R&D Program of China in the 13th 5-year plan. the motivation of developing the exa-scale computer and the need for establishing an eco-system for high performance computing in China will be presented. the major challenges in developing the exa-scale computer will be discussed. the major R&D activities of the new key project on HPC in the next 5 years will also be presented.

关键词： parallel processing High Performance computing parallel PROCESSING (COMPUTERS) REMEDIAL DESIGN current status

来源：评论

学校读者我要写书评

暂无评论

Efficiency of the Tegra K1 and X1 Systems-on-Chip for Classical Molecular Dynamics 14

Efficiency of the Tegra K1 and X1 Systems-on-Chip for Classi...

引用

international Workshop on parallel Optimization using/for Multi and Many-Core High Performance computing (POMCO) in conjunction with 14th international conference on High Performance computing and Simulation (HPCS)

作者： Nikolskiy, Vsevolod P. Stegailov, Vladimir V. Vecher, Vyacheslav S. Russian Acad Sci Joint Inst High Temperatures Izhorskaya st 13Bld 2 Moscow 125412 Russia Moscow Inst Phys & Technol Inst per. 9Moscow region Dolgoprudnyi Russia Nat Res Univ Higher Sch Econom Myasnizkaya st 20 Moscow 101000 Russia

ISBN: (纸本)9781509020881

Further development of high performance computing hardware and software is focused on energy and parallel efficiency that are both crucial for future exascale level of supercomputer performance. Real applications tests as well as small-scale benchmarks of new architectures are important for the choice of the best development strategies. ARM CPUs and NVIDIA GPUs are among the most energy efficient hardware. Recently both architectures have been combined in the NVIDIA Tegra systems-on-chip. In this work we benchmark the development boards with Tegra K1 and X1 both with the Roofline model toolkit as well as with different classical molecular dynamics algorithms implemented in LAMMPS. We consider the utilization of the single and double peak floating-point performance and the power and energy consumption of the corresponding Cortex-A15, Cortex-A57, Kepler and Maxwell cores.

关键词： System-on-chip

来源：评论

学校读者我要写书评

暂无评论

A Self-Organizing Algorithm for Community Structure Analysis in Complex Networks 17

A Self-Organizing Algorithm for Community Structure Analysis...

引用

17th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Sun, Hanlin Jie, Wei Sauer, Christian Ma, Sugang Han, Gang Xing, Wei Xian Univ Posts & Telecommun Big Data Res Ctr Xian Peoples R China Univ West London Sch Comp & Technol London England Northwestern Polytech Univ Dept Elect Sci & Technol Xian Peoples R China Univ Manchester CRUK Manchester Inst Manchester M13 9PL Lancs England

ISBN: (纸本)9781509022397

Community structure analysis is a critical task for complex network analysis. It helps us to understand the properties of the system that a complex network represents, and has significance to a wide range of real applications. the Label Propagation Algorithm (LPA) is currently the most popular community structure analysis algorithm due to its near linear time complexity. However, the performance of the LPA has proven to be unstable and the correctness of community assignment of nodes is unsatisfactory. In this paper a Self-Organizing Community Detection and Analytic Algorithm (SOCDA(2)) based on swarm intelligence is proposed. In the algorithm, a network is modeled as a swarm intelligence system, while each node within the network acts iteratively to join or leave communities based on a set of pre-defined node action rules, in order to improve the quality of the communities. When there is not a node changing its belonging community anymore, an optimal community structure will emerge as a result. A variety of experiments conducted on both synthesized and real-world networks have shown results which indicate that the proposed algorithm can effectively detect community structures and the performance is better than that of the LPA. In addition, the algorithm can be extended for overlapping community detection and be parallelized for large-scale network analysis.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Petri Nets for Modelling of Message Passing Middleware in Cloud computing Environments 16th

Petri Nets for Modelling of Message Passing Middleware in Cl...

引用

16th international conference on Computational Science and Its applications (ICCSA)

作者： Iakushkin, Oleg Shichkina, Yulia Sedova, Olga St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia St Petersburg Elect Univ LETI Dept Comp Sci & Engn St Petersburg Russia

ISBN: (纸本)9783319421087

Cloud systems allow to run parallel applications using solutions with distributed heterogeneous architecture. Software development for heterogeneous distributed environment requires a module-based design. the components in such module system are connected by means of telecommunications network enabling message passing. this article describes an interaction model for components in distributed applications. the model was designed based on the paradigm of Variable Speed Hybrid Petri Nets and allows to analyse system performance at various tiers: selection of the optimum approach to load balancing between components;making scaling decisions to enhance performance of certain modules;fine-tuning the interaction between system components. the model is not contingent on particular tools a user might employ to implement a solution;it also provides a monitoring data integration functionality. the model contains descriptions of standard messaging patterns linking components of distributed applications. these patterns include request-reply and publish-subscribe. Load balancing algorithms for various schemes of these patterns usage have been developed for a cloud environment.

关键词： Cloud services Messaging patterns Systems architecture Petri nets Messaging middleware distributed applications

来源：评论

学校读者我要写书评

暂无评论

distributed computing Infrastructure Based on Dynamic Container Clusters 16th

Distributed Computing Infrastructure Based on Dynamic Contai...

引用

16th international conference on Computational Science and Its applications (ICCSA)

作者： Korkhov, Vladimir Kobyshev, Sergey Krosheninnikov, Artem Degtyarev, Alexander Bogdanov, Alexander St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia

ISBN: (纸本)9783319421087

Modern scientific and business applications often require fast provisioning of an infrastructure tailored to particular application needs. In turn, actual physical infrastructure contains resources that might be underutilized by applications if allocated in dedicated mode (e.g., a process does not utilize provided CPU or network connection fully). Traditional virtualization technologies can solve the problem partially, however, overheads on bootstrapping a virtual infrastructure for each application and sharing physical resources might be significant. In this paper we propose and evaluate an approach to create and configure dedicated computing environment tailored to the needs of particular applications, which is based on light-weight virtualization also known as containers. We investigate available capabilities to model and create dynamic container-based virtual infrastructures sharing a common set of physical resources, and evaluate their performance on a set of test applications with different requirements.

关键词： Virtualization Containers Virtual cluster

来源：评论

学校读者我要写书评

暂无评论

Increasing the efficiency of code offloading in n-tier environments with code bubbling 2016

Increasing the efficiency of code offloading in n-tier envir...

引用

13th international conference on Mobile and Ubiquitous Systems: computing, Networking and Services, MobiQuitous 2016

作者： Berg, Florian Dürr, Frank Rothermel, Kurt Institute of Parallel and Distributed Systems University of Stuttgart Stuttgart70569 Germany

ISBN: (纸本)9781450347815

Code offloading strives for increasing the energy efficiency and execution speed of mobile applications on resource-constrained mobile devices. First approaches considered only a code offloading between two (or three) tiers, executing code either locally on the mobile device or remotely on a powerful server in the vicinity or in a distant cloud. However, new execution environments comprise multiple tiers, containing highly distributed heterogeneous resources. We present in this paper our Code Bubbling Offload System (CoBOS). CoBOS targets n-tier environments containing highly distributed heterogeneous resources with different performance characteristics and cost implications. In such n-tier environments, it is very costly for a resource-constrained mobile device to gather a global view on available resources. As a result, we propose the novel concept of code bubbling. Code bubbling moves code dynamically and adaptively towards more powerful and more distant tiers, enabling an efficient and scalable code offloading in n-tier environments. Each tier makes autonomous decisions to execute code in the tier or forward it further to the next tier. To support such a recursive escalation of code along autonomous tiers, CoBOS offloads self-contained offload requests that possess all of the required information for the processing. Our real-world evaluation shows that CoBOS decreases the energy consumption by 77% and the execution time by 83% for code offloading in n-tier environments. © 2016 ACM.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Keynote Speech 1: Big Data on Clouds and HPC

Keynote Speech 1: Big Data on Clouds and HPC

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Geoffrey Fox Indiana University Bloomington Bloomington IN US

ISBN: (纸本)9781509050826

We review several questions at the intersection of Big Data, Clouds and HPC with the large scale simulations usually run on supercomputers and the target of the exascale initiative. We base this on an analysis of many big data and simulation problems and a set of properties -the Big Data Ogres -characterizing them where we distinguish data and model properties. We consider broad topics: What are the application and user requirements? e.g. is the data streaming, how similar are commercial and scientific requirements? What is execution structure of problems? e.g. is it dataflow or more like MPI? Should we use threads or processes? Is execution pleasingly parallel? What about the many choices for infrastructure and middleware? Should we use classic HPC cluster, Docker or OpenStack? Where are Big Data (Apache) approaches superior/inferior to those familiar from Grid and HPC work? the choice of language -C++, Java, Scala, Python, R highlights performance v. productivity trade-offs. What is actual performance of Big Data implementations and what are good benchmarks? Is software sustainability important and is the Apache model a good approach to this? the difference between capability and capacity computing on HPC clusters.

关键词： Big Data cloud computing middleware parallel machines pattern clustering big data High Performance computing Middleware parallel machines Cloud computing Cluster Analysis Clouds

来源：评论

学校读者我要写书评

暂无评论

Keynote Speech 3: the Era of Big Data and Cognitive computing

Keynote Speech 3: The Era of Big Data and Cognitive Computin...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Hui Lei International Business Machines Corp Armonk NY US

ISBN: (纸本)9781509050826

Summary form only given. Big data and cognitive computing are driving fundamental changes in technology, business, and society. With its exponentially increasing volume, velocity and variety, big data is hailed as the world's new natural resource. It promises to be for the 21st century what steam power was for the 18th, electricity for the 19th, and oil and gas for the 20th. the biggest value of big data lies in the deep, actionable insights that can be derived from the raw data and leveraged for competitive advantages. Cognitive computing is a key enabling technology for turning big data into insights. Different from the traditional programmable systems, cognitive systems are able to scale and extend human knowledge, reason with purpose, and learn and improve over time. the rise of cognitive systems represents the dawn of a new era of computing, whose focus has shifted from automating the world to understanding the world. In this talk, I will discuss the implications of big data and cognitive computing. I will reflect on our experience at IBM building the Watson Health Cloud, and discuss how big data and cognitive computing can come together to enable innovative health solutions that tackle many of the clinical, societal, and economic issues faced by today's health industry. I will present use cases, highlight the challenges, describe our approaches, and relate to client experiences as appropriate.

关键词： Big Data cognitive systems health care big data cognitive function Health Care bulk velocity

来源：评论

学校读者我要写书评

暂无评论

Performance Measurement on Scale-Up and Scale-Out Hadoop with Remote and Local File Systems

Performance Measurement on Scale-Up and Scale-Out Hadoop wit...

引用

IEEE international conference on Cloud computing, CLOUD

作者： Zhuozhao Li Haiying Shen Department of Electrical and Computer Engineering Clemson University Clemson SC

MapReduce is a popular computing model for parallel data processing on large-scale datasets, which can vary from gigabytes to terabytes and petabytes. though Hadoop MapReduce normally uses Hadoop distributed File System (HDFS) local file system, it can be configured to use a remote file system. then, an interesting question is raised: for a given application, which is the best running platform among the different combinations of scale-up and scale-out Hadoop with remote and local file systems. However, there has been no previous research on how different types of applications (e.g., CPU-intensive, data-intensive) with different characteristics (e.g., input data size) can benefit from the different platforms. thus, in this paper, we conduct a comprehensive performance measurement of different applications on scale-up and scaleout clusters configured with HDFS and a remote file system (i.e., OFS), respectively. We identify and study how different job characteristics (e.g., input data size, the number of file reads/writes, and the amount of computations) affect the performance of different applications on the different platforms. this study is expected to provide a guidance for users to choose the best platform to run different applications with different characteristics in the environment that provides both remote and local storage, such as HPC cluster.

关键词： Random access memory Measurement File systems Program processors distributed databases Servers Computer architecture

来源：评论

学校读者我要写书评

暂无评论

Operating system plan9 as the implementation of the grid ideology 7

Operating system plan9 as the implementation of the grid ide...

引用

7th international conference distributed computing and Gridtechnologies in Science and Education, GRID 2016

作者： Gevorkyan, M.N. Gostev, I.M. Korolkova, A.V. Kulyabov, D.S. Sevastianov, L.A. RUDN University Peoples Friendship University of Russia 6 Miklukho-Maklaya street Moscow117198 Russia National Research University Higher School of Economics 20 Myasnitskaya street Moscow101000 Russia Laboratory of Information Technologies Joint Institute for Nuclear Research 6 Joliot-Curie street Dubna Moscow Region141980 Russia Bogoliubov Laboratory of Theoretical Physics Joint Institute for Nuclear Research 6 Joliot-Curie street Dubna Moscow Region141980 Russia

When we organize parallel computations on a cluster system, the computer system structure is not hidden from the user, and should be taken into account while writing parallel programs. GRID ideology introduces an additional level of abstraction and makes it possible to link together heterogeneous computing systems. In fact, the inability to control the operating environment makes developers to create superfluous infrastructure at the application level. We offer to go down to the below level and to implement the necessary functionality within the operating environment kernel. Plan9 operating system has the immanent structure necessary for the implementation of GRID ideology. the main architectural elements of the operating system allow you to use all the resources of the remote computer as the local resources. © 2016 Migran N. Gevorkyan, Ivan M. Gostev, Anna V. Korolkova, Dmitry S. Kulyabov, Leonid A. Sevastianov.

关键词： Computer operating systems

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178页 << < 60 61 62 63 64 65 66 67 68 69 > >>

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：