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

7,053 篇 会议
91 篇 期刊文献
52 册 图书

馆藏范围

7,196 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,967 篇 工学
- 3,414 篇 计算机科学与技术...
- 1,569 篇 信息与通信工程
- 1,427 篇 软件工程
- 1,051 篇 电气工程
- 241 篇 控制科学与工程
- 122 篇 电子科学与技术（可...
- 93 篇 网络空间安全
- 76 篇 动力工程及工程热...
- 74 篇 仪器科学与技术
- 64 篇 生物工程
- 52 篇 机械工程
- 37 篇 安全科学与工程
- 34 篇 建筑学
- 34 篇 土木工程
- 33 篇 测绘科学与技术
- 33 篇 交通运输工程
- 31 篇 生物医学工程（可授...
565 篇 管理学
- 417 篇 管理科学与工程(可...
- 187 篇 图书情报与档案管...
- 144 篇 工商管理
520 篇 理学
- 314 篇 数学
- 95 篇 物理学
- 74 篇 生物学
- 73 篇 系统科学
- 66 篇 统计学（可授理学、...
100 篇 法学
- 52 篇 社会学
- 49 篇 法学
63 篇 医学
- 37 篇 基础医学(可授医学...
- 31 篇 公共卫生与预防医...
42 篇 经济学
- 41 篇 应用经济学
26 篇 文学
25 篇 教育学
12 篇 农学
6 篇 军事学
2 篇 艺术学

主题

1,160 篇 distributed comp...
419 篇 software enginee...
361 篇 cloud computing
360 篇 artificial intel...
312 篇 computer archite...
303 篇 computer network...
284 篇 social networkin...
269 篇 protocols
247 篇 computer science
236 篇 computational mo...
221 篇 wireless sensor ...
212 篇 scalability
205 篇 peer to peer com...
205 篇 resource managem...
196 篇 routing
190 篇 bandwidth
189 篇 servers
188 篇 application soft...
183 篇 distributed data...
166 篇 grid computing

机构

110 篇 beijing univ pos...
90 篇 state key labora...
12 篇 department of co...
11 篇 college of compu...
10 篇 tsinghua univers...
10 篇 poznan supercomp...
10 篇 school of comput...
10 篇 department of co...
10 篇 beijing universi...
9 篇 inria
9 篇 beijing universi...
9 篇 research institu...
9 篇 rissho universit...
9 篇 tsinghua univ pe...
9 篇 institute of net...
9 篇 school of cyber ...
9 篇 institute of com...
8 篇 georgia inst tec...
8 篇 department of co...
8 篇 institute of net...

作者

25 篇 yang yang
16 篇 huang lican
16 篇 lican huang
14 篇 wehrle klaus
13 篇 gao zhipeng
12 篇 dustdar schahram
12 篇 buyya rajkumar
12 篇 rothermel kurt
11 篇 duerr frank
11 篇 wu jan-jan
11 篇 rajkumar buyya
11 篇 wang wei
11 篇 liu pangfeng
11 篇 teruhisa hochin
11 篇 qi qi
10 篇 ming chen
10 篇 hoefler torsten
10 篇 m. takizawa
10 篇 cheng shiduan
10 篇 schahram dustdar

语言

6,953 篇 英文
199 篇 其他
48 篇 中文

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

共 7196 条记录，以下是1961-1970 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：

DCIGAN: A distributed Class-Incremental Learning Method Based on Generative Adversarial Networks

DCIGAN: A Distributed Class-Incremental Learning Method Base...

引用

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

作者： Hongtao Guan Yijie Wang Xingkong Ma Yongmou Li Science and Technology on Parallel and Distributed Laboratory College of Computer National University of Defense Technology Changsha Hunan P.R.China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Class incremental learning has received wide attention due to its better adaptability to the changing characteristics of online learning. However, data cannot be shared between organizations in the data isolated islands scenario. Existing solutions cannot adapt to incremental classes without aggregating data. In this paper, we propose a distributed class-incremental learning framework, called DCIGAN. It uses GAN generators to store the information of past data and continuously update GAN parameters with new data. In particular, we proposed CIGAN to ensure that the distribution of generated pseudo data is as close as possible to the real data on a single node, which guarantees the accuracy of class-incremental learning. Furthermore, we propose GF, a generators fusion method to integrate local generators of multi-nodes into a new global generator. To evaluate the performance of DCIGAN, we conduct experiments on six datasets under various parameter settings on both two and multi nodes distributed scenarios. Extensive experiments confirm that DCIGAN outperform the general baselines and achieve classification accuracy closes to the method of data aggregating.

关键词： Generators Generative adversarial networks distributed databases Diseases Servers Hospitals Training

来源：评论

学校读者我要写书评

暂无评论

Traffic Image Acquisition and Compression Technology in Vehicular Ad Hoc Network

Traffic Image Acquisition and Compression Technology in Vehi...

引用

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

作者： Fu Pang Xiangyu Bai College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing Inner Mongolia University Hohhot China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

With the frequent occurrence of traffic accidents, the timely acquisition of traffic images using Vehicular Ad Hoc Network (VANET) technology is of great significance for traffic rescue and evidence preservation. However, due to the limited bandwidth of VANET, the amount of data transmitted is limited. In response to this problem, this paper designs an image acquisition algorithm. The algorithm selects several images from the driving recorder of the vehicles around the accident. These images are transmitted to the traffic management department. In addition, the selected images have strong temporal and spatial correlation, so they can be compressed by compressed sensing technology to further reduce the amount of data. Therefore, the method of processing images on the vehicle node using compressed sensing technology are proposed. Finally, the effectiveness of the image acquisition algorithm is verified by simulation experiments.

关键词： Accidents Image coding Roads Compressed sensing Vehicular ad hoc networks Bandwidth Cameras

来源：评论

学校读者我要写书评

暂无评论

MDDRSPF: A Model Driven distributed Real-Time Stream Processing Framework

MDDRSPF: A Model Driven Distributed Real-Time Stream Process...

引用

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

作者： Yijun Wen Li Zhang Cheng Wang School of Software Tsinghua University & Naval Research Academy (NVRA) Beijing China School of Software Tsinghua University Beijing China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Some enterprises have demands for distributed stream processing framework to manage and process diverse business services. But their business is usually user-oriented, the access data sources and outputs are heterogeneous and need to be configurable, and the user-oriented service mode requires the platform have the ability to deploy new algorithm dynamically and provide on-demand services. As we know, there is no system that can meet all these requirements, hence a Model Driven distributed Real-time Stream Processing Framework is proposed. By building project and task models, the functional model is separated from the implementation platform. The framework support multi-source heterogeneous data input and configurable output, on-demand services based on user's request, and algorithm dynamic loading. Service oriented architecture is deployed to lower the threshold of algorithm development and deployment. Furthermore, the functionality and performance is evaluated with a practical case to verify whether the system can meet the needs of practical application.

关键词： Task analysis Data models Real-time systems Load modeling Computational modeling Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

Using Predictive Monitoring Models in Cloud computing Systems 21st

Using Predictive Monitoring Models in Cloud Computing System...

引用

21st international conference on distributed and Computer and Communication Networks (DCCN)

作者： Kucherova, Kristina Mescheryakov, Serg Shchemelinin, Dmitry Peter Great St Petersburg Polytech Univ Polytekhn Skaya 29 St Petersburg 195251 Russia

ISBN: (纸本)9783319994475;9783319994468

Predictive modeling is an important part of the monitoring process in cloud computing systems that helps to improve the service availability for the customers. This paper describes two industrial examples of predictive monitoring models for database disk space utilization and Java memory leaks. Practical recommendations are given to improve the forecast accuracy, which can also be used in the other similar cases. The results of this work are validated in the open source monitoring system and are implemented in three big international telecommunications companies.

关键词： Predictive monitoring Forecast accuracy Cloud computing Globally distributed infrastructure High loaded system Big data Database Disk space utilization File autogrowth Java memory leak Internet applications Service availability

来源：评论

学校读者我要写书评

暂无评论

High-Performance Dense Tucker Decomposition on GPU Clusters

High-Performance Dense Tucker Decomposition on GPU Clusters

引用

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

作者： Choi, Jee Liu, Xing Chakaravarthy, Venkatesan IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA IBM India Res Lab New Delhi India

ISBN: (纸本)9781538683842

The dense Tucker decomposition method is one of the most popular algorithms for analyzing and compressing data with multi-way relationship. Its execution time is typically dominated by dense matrix multiplication operations, which makes it well-suited for GPU acceleration. State-of-the-art distributed dense Tucker implementations for CPU clusters adopt multi-dimensional partitioning that optimizes for storage and communication. This, however, leads to smaller matrix dimensions that result in under-utilizing the GPU resources. In this paper, we present our optimized implementation and performance analysis of dense Tucker decomposition on a multi-GPU cluster. We propose three key optimizations: a new partitioning strategy that improves performance for GPUs, a new tensor matricization layout that halves the number of communication and matricization steps, and a variation of the randomized SVD algorithm to overcome the eigenvalue calculation bottleneck that arises from the high speedup gained from GPU acceleration. When compared to the state-of-the-art TuckerMPI library, our best GPU implementation, which employs all three optimizations described above, achieves up to 11.8x speedup on 64 nodes. Our best CPU implementation, which also employs all three optimizations, achieves up to 3.6x speedup over TuckerMPI on 64 nodes. When we compare our best GPU implementation to our best CPU implementation, the speedup ranges from 2.1x to 3.6x on a single node, and from 1.8x to 3.3x on 64 nodes, depending on the input data set.

关键词： tensor decomposition Tucker GPU MPI distributed high-performance computing HPC HOSVD

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Service Oriented Network Provisioning in Ultra-Scale Systems 1

引用

23rd international conference on Parallel and distributed computing (Euro-Par)

作者： Kimovski, Dragi Ristov, Sashko Matha, Roland Prodan, Radu Univ Innsbruck Inst Informat Distributed & Parallel Syst Innsbruck Austria

ISBN: (数字)9783319751788

ISBN: (纸本)9783319751788;9783319751771

The paradigm of ultra-scale computing has been recently pushed forward by the current trends in distributed computing. This novel architecture concept is focused towards a federation of multiple geographically distributed heterogeneous systems under a single system image, thus allowing efficient deployment and management of very complex architectures applications. To enable sustainable ultra-scale computing, there are multiple major challenges, which have to be tackled, such as, improved data distribution, increased systems scalability, enhanced fault tolerance, elastic resource management, low latency communication and etc. Regrettably, the current research initiatives in the area of ultra-scale computing are in a very early stage of research and are predominantly concentrated on the management of the computational and storage resources, thus leaving the networking aspects unexplored. In this paper we introduce a promising new paradigm for cluster-based Multi-objective service-oriented network provisioning for ultra-scale computing environments by unifying the management of the local communication resources and the external inter-domain network services under a single point of view. We explore the potentials for representing the local network resources within a single distributed or parallel system and combine them together with the external communication services.

关键词： Inter-domain network provisioning Multi-objective optimization Machine learning

来源：评论

学校读者我要写书评

暂无评论

international conference on Wireless and Mobile computing, networking and Communications

International Conference on Wireless and Mobile Computing, N...

引用

13th IEEE international conference on Wireless and Mobile computing, networking and Communications, WiMob 2017

ISBN: (纸本)9781538638392

The proceedings contain 112 papers. The topics discussed include: superposition coding in alternate DF relaying systems with inter-relay interference cancellation;transmit antenna selection in OFDM relay system as a solution for energy efficiency improvement;reliable multipath multi-channel route migration over multi link-failure in wireless ad hoc networks;WebShawn, simulating wireless sensors networks from the web;a distributed data management scheme for industrial IoT environments;work in progress: compilation of environmental data through portable low-cost sensors with delay-tolerant mobile ad-hoc networks;and optimal aggregated ConvergeCast scheduling with an SINR interference model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Performance Implications of Big Data in Scalable Deep Learning: On the Importance of Bandwidth and Caching

Performance Implications of Big Data in Scalable Deep Learni...

引用

IEEE international conference on Big Data (Big Data)

作者： Hodak, Miro Ellison, David Seidel, Peter Dholakia, Ajay Lenovo Data Ctr Grp Morrisville NC 27560 USA

ISBN: (纸本)9781538650356

Deep learning techniques have revolutionized many areas including computer vision and speech recognition. While such networks require tremendous amounts of data, the requirement for and connection to Big Data storage systems is often undervalued and not well understood. In this paper, we explore the relationship between Big Data storage, networking, and Deep Learning workloads to understand key factors for designing Big Data/Deep Learning integrated solutions. We find that storage and networking bandwidths are the main parameters determining Deep Learning training performance. Local data caching can provide a performance boost and eliminate repeated network transfers, but it is mainly limited to smaller datasets that fit into memory. On the other hand, local disk caching is an intriguing option that is overlooked in current state-of-the-art systems. Finally, we distill our work into guidelines for designing Big Data/Deep Learning solutions.

关键词： big data deep learning distributed computing high performance network

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the international conference for High Performance computing, networking, Storage and Analysis, SC 2017

Proceedings of the International Conference for High Perform...

引用

international conference for High Performance computing, networking, Storage and Analysis, SC 2017

ISBN: (纸本)9781450351140

The proceedings contain 64 papers. The topics discussed include: redesigning CAM-SE for peta-scale climate modeling performance and ultra-high resolution on sunway TaihuLight;18.9-Pflops nonlinear earthquake simulation on sunway TaihuLight: enabling depiction of 18-hz and 8-meter scenarios;massively parallel 3D image reconstruction;LocoFS: a loosely-coupled metadata service for distributed file systems;tagit: an integrated indexing and search service for file systems;a configurable rule based classful token bucket filter network request scheduler for the luster file system;and understanding error propagation in deep learning neural network (DNN) accelerators and applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Parallel distributed Schedulers for Scalable Photonic Integrated Packet Switching

Parallel Distributed Schedulers for Scalable Photonic Integr...

引用

international conference on Photonics in Switching and computing (PSC)

作者： Andreades, Paris Zervas, Georgios UCL Opt Networks Grp Elect & Elect Engn London England

ISBN: (纸本)9781538693926

As data centre traffic dynamics are changing, optical networking is becoming increasingly important for low-latency, high bandwidth intra-data centre communication. Nanosecond-reconfigurable, scalable photonic switch fabrics and advances in photonic integration are key enablers for optical packet switching. However, the control plane and in particular the switch scheduler is believed to be a critical factor on packet latency and scalability. To that end, we report a low-latency scheduler for Clos-network switch fabrics based on a fixed path assignment scheme and parallel and distributed path arbitration. Cycle-accurate network emulation results show nanosecond average latency at input port loads up to 60% of capacity for a 256x256 switch size. In comparison to previous work, the scheduler can now control a switch 8 times the size at double the input port saturation load for the same average latency. Scaling the switch from 16 to 256 ports shows only a small drop in saturation load from 70% to 60%. Also fairness on a per flow basis is demonstrated.

关键词： switch scheduling Clos-network switch optical packet switching

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 << < 193 194 195 196 197 198 199 200 201 202 > >>

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：