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

8,700 篇 会议
177 篇 期刊文献
13 册 图书

馆藏范围

8,890 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,765 篇 工学
- 4,262 篇 计算机科学与技术...
- 1,768 篇 软件工程
- 976 篇 电气工程
- 735 篇 信息与通信工程
- 291 篇 控制科学与工程
- 213 篇 电子科学与技术（可...
- 109 篇 生物医学工程（可授...
- 105 篇 生物工程
- 101 篇 机械工程
- 84 篇 仪器科学与技术
- 73 篇 动力工程及工程热...
- 66 篇 网络空间安全
- 58 篇 力学（可授工学、理...
- 43 篇 安全科学与工程
- 39 篇 材料科学与工程（可...
- 35 篇 交通运输工程
- 35 篇 环境科学与工程（可...
982 篇 理学
- 625 篇 数学
- 210 篇 物理学
- 124 篇 系统科学
- 117 篇 生物学
- 100 篇 统计学（可授理学、...
- 52 篇 化学
563 篇 管理学
- 420 篇 管理科学与工程(可...
- 183 篇 图书情报与档案管...
- 169 篇 工商管理
88 篇 医学
- 58 篇 临床医学
- 45 篇 基础医学(可授医学...
55 篇 法学
- 35 篇 社会学
44 篇 经济学
- 43 篇 应用经济学
22 篇 农学
16 篇 教育学
16 篇 文学
4 篇 军事学
3 篇 艺术学

主题

1,121 篇 distributed comp...
750 篇 concurrent compu...
592 篇 memory managemen...
552 篇 computational mo...
538 篇 computer archite...
471 篇 parallel process...
425 篇 cloud computing
371 篇 computer science
340 篇 random access me...
315 篇 scalability
295 篇 application soft...
295 篇 memory
269 篇 hardware
248 篇 bandwidth
246 篇 servers
245 篇 message passing
234 篇 costs
228 篇 resource managem...
222 篇 high performance...
220 篇 runtime

机构

26 篇 institute of com...
19 篇 university of ch...
17 篇 georgia inst tec...
14 篇 tsinghua univers...
13 篇 school of comput...
13 篇 oak ridge natl l...
13 篇 ohio state univ ...
11 篇 lawrence berkele...
11 篇 univ chinese aca...
11 篇 pacific northwes...
11 篇 the islamic univ...
10 篇 college of compu...
10 篇 ibm thomas j. wa...
10 篇 lawrence berkele...
10 篇 ohio state univ ...
10 篇 institute of inf...
10 篇 department of co...
10 篇 tsinghua univ pe...
10 篇 college of compu...
10 篇 intel corporatio...

作者

17 篇 p. banerjee
17 篇 hai jin
13 篇 li dongsheng
13 篇 liu jie
13 篇 jin hai
11 篇 a. choudhary
10 篇 dongarra jack
10 篇 p. sadayappan
10 篇 wang wei
9 篇 hoefler torsten
9 篇 dongsheng li
9 篇 liu yang
9 篇 dou yong
9 篇 lai zhiquan
9 篇 nong xiao
9 篇 j. saltz
8 篇 beineke kevin
8 篇 zhiyi huang
8 篇 lumsdaine andrew
8 篇 mitsuhisa sato

语言

8,792 篇 英文
68 篇 其他
27 篇 中文
4 篇 俄文
1 篇 西班牙文
1 篇 葡萄牙文
1 篇 土耳其文

检索条件"任意字段=Distributed Memory Computing Conference"

共 8890 条记录，以下是41-50 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：

Towards Optimizing Cost and Performance for Parallel Workloads in Cloud computing

Towards Optimizing Cost and Performance for Parallel Workloa...

引用

15th International conference on Cloud computing and Services Science, CLOSER 2025

作者： Maas, William Rossi, Fábio Diniz Luizelli, Marcelo C. Navaux, Philippe O.A. Lorenzon, Arthur F. Institute of Informatics Federal University of Rio Grande do Sul Brazil Federal Institute Farroupilha Campus Alegrete Brazil Federal University of Pampa Campus Alegrete Brazil

ISBN: (纸本)9789897587474

The growing popularity of data-intensive applications in cloud computing necessitates a cost-effective approach to harnessing distributed processing capabilities. However, the wide variety of instance types and configurations available can lead to substantial costs if not selected based on the parallel workload requirements, such as CPU and memory usage and thread scalability. This situation underscores the need for scalable and economical infrastructure that effectively balances parallel workloads’ performance and expenses. To tackle this issue, this paper comprehensively analyzes performance, costs, and trade-offs across 18 parallel workloads utilizing 52 high-performance computing (HPC) optimized instances from three leading cloud providers. Our findings reveal that no single instance type can simultaneously offer the best performance and the lowest costs across all workloads. Instances that excel in performance do not always provide the best cost efficiency, while the most affordable options often struggle to deliver adequate performance. Moreover, we demonstrate that by customizing instance selection to meet the specific needs of each workload, users can achieve up to 81.2% higher performance and reduce costs by 95.5% compared to using a single instance type for every workload. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Parallel processing systems

来源：评论

学校读者我要写书评

暂无评论

Research on Big Data distributed computing Model and Algorithm Optimization for Complex Network Analysis

Research on Big Data Distributed Computing Model and Algorit...

引用

Digital Analysis and Processing, Intelligent Computation (DAPIC), International conference on

作者： Aiting Sun Liaoning Vocational College of light industry Liaoning China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

With the advent of the era of big data, the traditional stand-alone computing model can no longer meet the needs of complex network analysis, and the distributed computing model provides a new solution. This paper first introduces the importance of complex network analysis and the challenges brought by big data, then discusses the application of distributed computing model in complex network analysis in detail, and focuses on the distributed computing algorithm based on MapReduce. Then, this paper puts forward an optimization strategy of distributed community detection algorithm based on modularity optimization. This strategy performs community detection tasks in parallel through MapReduce framework, and optimizes community division through iterative updating to maximize modularity. The experimental results show that the optimized algorithm has a significant improvement in computing time, accuracy and resource consumption. The distributed computing model based on MapReduce framework and its optimization strategy have obvious advantages in dealing with large-scale complex networks. It can not only improve the calculation efficiency and accuracy, but also reduce the resource consumption, which provides an efficient and feasible solution for complex network analysis.

关键词： Analytical models Accuracy Computational modeling memory management Complex networks Big Data Data models distributed computing Detection algorithms Optimization

来源：评论

学校读者我要写书评

暂无评论

Adaptive Gradient Data Partition and Route Selection for distributed DNN Training 20th

Adaptive Gradient Data Partition and Route Selection for D...

引用

20th IFIP WG 10.3 International conference on Network and Parallel computing, NPC 2024

作者： Chai, Bo Tan, Xiaobin Yuan, Shenzhi Jia, Guangge Meng, Qiushi Wang, Weifeng Zhu, Shiyin University of Science and Technology of China Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China H3C Technologies Co. Limited Beijing China

ISBN: (纸本)9789819628636

As the scale of distributed training for Deep Neural Network (DNN) increases, communication has become a critical performance bottleneck in data center networks. In-Network Aggregation (INA) can accelerate aggregating gradients process, the critical communication bottleneck in distributed DNN training. Due to the limited processing capacity of network switch, existing aggregation approaches have turned to a combination of INA and Parameter Server (PS) methods. However, these approaches employ a fixed partitioning of the gradient data, leading to suboptimal performance. This paper proposes GPRS, an adaptive gradient aggregation framework for distributed DNN training, which adaptively combines the line-rate processing of INA and large memory capacity of PS. We present an adaptive gradient data partition scheme, which divides the gradient data into INA and PS aggregation. We propose a heuristic algorithm that determines the aggregation route selection by assigning priority to the available network paths. To validate our approach, we build a real-world experimental testbed and implement the proposed framework. Experimental results show that it can overcome the limitations of traditional INA-only methods and reduce communication time by 15% ∼ 52% for DNN training of varying scales. © IFIP International Federation for Information Processing 2025.

关键词： Data aggregation

来源：评论

学校读者我要写书评

暂无评论

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615278

The proceedings contain 131 papers. The special focus in this conference is on Algorithms and Architectures for Parallel Processing. The topics include: MARO: Enabling Full MPI Automatic Refactoring in DSL-Based Programming Framework;SSC: An SRAM-Based Silence computing Design for On-chip memory;TP-BFT: A Faster Asynchronous BFT Consensus with Parallel Structure;LTP: A Lightweight On-Chip Temporary Prefetcher for Data-Dependent memory Accesses;A Neural Network-Based PUF Protection Method Against Machine Learning Attack;Compression Format and Systolic Array Structure Co-design for Accelerating Sparse Matrix Multiplication in DNNs;multidimensional Intrinsic Identity Construction and Dynamic Seamless Authentication Schemes in IoT Environments;invisible Backdoor Attack with Image Contours Triggers;finestra: Multi-aggregator Swarm Learning for Gradient Leakage Defense;DIsFU: Protecting Innocent Clients in Federated Unlearning;multiple-Round Aggregation of Abstract Semantics for Secure Heterogeneous Federated Learning;dynamic Privacy Protection with Large Language Model in Social Networks;a Dynamic Symmetric Searchable Encryption Scheme for Rapid Conjunctive Queries;a Data Watermark Scheme Base on Data Converted Bitmap for Data Trading;distributed Incentive Algorithm for Fine-Grained Offloading in Vehicular Ad Hoc Networks;mitigating Over-Unlearning in Machine Unlearning with Synthetic Data Augmentation;AW-YOLOv9: Adverse Weather Conditions Adaptation for UAV Detection;efficient and Privacy-Preserving Ranking-Based Federated Learning;on-Chain Dynamic Policy Evaluation for Decentralized Access Control;DPG-FairFL: A Dual-Phase GAN-Based Defense Framework Against Image-Based Fairness Data Poisoning Attacks in Federated Learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615414

关键词：

来源：评论

学校读者我要写书评

暂无评论

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615476

关键词：

来源：评论

学校读者我要写书评

暂无评论

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615506

关键词：

来源：评论

学校读者我要写书评

暂无评论

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615445

关键词：

来源：评论

学校读者我要写书评

暂无评论

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

24th International Conference on Algorithms and Architecture...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

ISBN: (纸本)9789819615247

关键词：

来源：评论

学校读者我要写书评

暂无评论

StressViT: Splitting and Compressing Vision Transformer Through Edge-Cloud Collaboration 27th

StressViT: Splitting and Compressing Vision Transformer Thr...

引用

27th International conference on Pattern Recognition, ICPR 2024

作者： Lin, Changyao Liu, Yi Li, Xiangyu Li, Chengxiang Zhang, Hao Jin, Jing Liu, Jie Faculty of Computing Harbin Institute of Technology Harbin China School of Astronautics Harbin Institute of Technology Harbin China International Research Institute for Artificial Intelligence Harbin Institute of Technology Shenzhen China Nanjing Research Center Huawei Technologies Co. Ltd Nanjing China

ISBN: (纸本)9783031781681

The emergence of ViT demonstrates the viability of Transformer in the field of computer vision, rivaling or even surpassing the performance of some CNN-based models. However, ViT’s substantial computation and memory demands present deployment challenges on resource-constrained devices. While various lightweight ViT techniques have been developed, they do not combine collaboration between heterogeneous devices for model splitting. Especially for large Transformer-based models, single-device deployment is infeasible, necessitating model splitting across multiple, even heterogeneous devices for distributed inference, and the optimal split point becomes crucial. Therefore, for a typical heterogeneous scenario of edge-cloud, we propose StressViT to split and compressvisual Transformer through edge-cloud collaboration. StressViT considers the disparities in computility and memory between edge and cloud environments, striving to improve inference accuracy while satisfying memory and compression constraints. Evaluations on four heterogeneous devices and two datasets confirm the efficacy of StressViT, achieving nearly 50% reduction of end-to-end latency with almost no loss of accuracy. StressViT can also be applied to homogeneous devices for edge-edge or cloud-cloud splitting, and can be easily extended to split across more than two devices. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cloud platforms

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 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：