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

952 篇 会议
20 篇 期刊文献
2 册 图书

馆藏范围

974 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

653 篇 工学
- 595 篇 计算机科学与技术...
- 238 篇 软件工程
- 190 篇 电气工程
- 76 篇 电子科学与技术（可...
- 61 篇 信息与通信工程
- 31 篇 控制科学与工程
- 23 篇 动力工程及工程热...
- 11 篇 机械工程
- 11 篇 仪器科学与技术
- 8 篇 生物医学工程（可授...
- 7 篇 力学（可授工学、理...
- 7 篇 环境科学与工程（可...
- 6 篇 安全科学与工程
- 5 篇 材料科学与工程（可...
- 5 篇 建筑学
- 5 篇 交通运输工程
- 5 篇 生物工程
- 5 篇 网络空间安全
91 篇 理学
- 53 篇 数学
- 27 篇 系统科学
- 18 篇 物理学
- 8 篇 生物学
- 6 篇 统计学（可授理学、...
- 5 篇 化学
88 篇 管理学
- 76 篇 管理科学与工程(可...
- 31 篇 工商管理
- 14 篇 图书情报与档案管...
10 篇 经济学
- 10 篇 应用经济学
8 篇 法学
- 7 篇 社会学
6 篇 医学
4 篇 教育学
- 4 篇 教育学
3 篇 文学
2 篇 农学
2 篇 军事学

主题

75 篇 computer archite...
62 篇 hardware
60 篇 parallel process...
55 篇 multicore proces...
48 篇 computational mo...
37 篇 concurrent compu...
36 篇 high performance...
34 篇 instruction sets
34 篇 multi-core
33 篇 graphics process...
31 篇 scalability
31 篇 cloud computing
30 篇 parallel program...
29 篇 programming
29 篇 program processo...
29 篇 graphics process...
27 篇 kernel
25 篇 embedded systems
24 篇 conferences
24 篇 resource managem...

机构

9 篇 ohio state univ ...
5 篇 saitama univ gra...
4 篇 ohio state univ ...
3 篇 saitama universi...
3 篇 vienna universit...
3 篇 oak ridge natl l...
3 篇 graduate school ...
3 篇 fraunhofer igd t...
3 篇 center for compu...
3 篇 karlsruhe instit...
3 篇 oak ridge natl l...
3 篇 beihang univ sch...
2 篇 penn state univ ...
2 篇 uppsala univ upp...
2 篇 seoul natl univ ...
2 篇 coll william & m...
2 篇 china university...
2 篇 waseda univ dept...
2 篇 tsinghua univers...
2 篇 national univers...

作者

6 篇 takuya azumi
6 篇 panda d. k.
6 篇 azumi takuya
5 篇 subramoni hari
5 篇 shingo igarashi
5 篇 benini luca
4 篇 tatsuya horiguch...
4 篇 tasuku ishigooka
4 篇 petiton serge
4 篇 el-ghazawi tarek
4 篇 sato mitsuhisa
4 篇 amano hideharu
3 篇 liu bo
3 篇 klasky scott
3 篇 dongarra jack
3 篇 varbanescu ana l...
3 篇 qian depei
3 篇 sriram krishnamo...
3 篇 weichslgartner a...
3 篇 alam sadaf r.

语言

969 篇 英文
4 篇 其他
1 篇 中文

检索条件"任意字段=IEEE International Workshop on Multi-/Many-core Computing Systems"

共 974 条记录，以下是61-70 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：

Message from the Chairs: Welcome to the 2022 ieee 15th international Symposium on embedded multicore/many-core systems-on-Chip (ieee MCSoC-2022)

Message from the Chairs: Welcome to the 2022 IEEE 15th Inter...

引用

ieee international Symposium on Embedded multicore Socs (MCSoC)

The 2022 ieee 15 th international Symposium on Embedded multicore/many-core systemson-Chip (MCSoC-2022) is an annual international symposium favored by the Universiti Sains Malaysia (USM) and the Technical Committee on Microprocessors and Micro-computers of the ieee Computer Society in cooperation with the ieee Singapore Section. MCSoC 2022 is hosted in Penang - a charming island in Malaysia - at Universiti Sains Malaysia (USM). There is growing confidence that future massively-parallel computer systems will be based on connectionist models and the innovative design of interconnection networks, processor architecture, applications, and software tools for embedded multi-core systems-on-chip will play a crucial role in our understanding the future systems. Along with Industry 4.0, the Internet of Things, cloud computing, data-centric computing through the Internet along with artificial intelligence become more and more popular. Therefore, the required computing power is incredibly increasing every moment. The rise of artificial intelligence innovation in recent years is encountering efficiency of power, online adaptation, and architectural and design issues. This edition of MCSoC offers new tracks on artificial intelligence on-chip learning and neuromorphic computing together with nine tracks on SoC design and application to bring new and potent methods for design from devices to applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SCALABLE ALGORITHMS FOR CONVEX CLUSTERING

SCALABLE ALGORITHMS FOR CONVEX CLUSTERING

引用

ieee Data Science and Learning workshop (DSLW)

作者： Zhou, Weilian Yi, Haidong Mishne, Gal Chi, Eric NC State Univ Dept Stat Raleigh NC 27607 USA Univ N Carolina Dept Comp Sci Chapel Hill NC 27599 USA Univ Calif San Diego Halicioglu Data Sci Inst La Jolla CA 92093 USA

ISBN: (纸本)9781665428255

Convex clustering is an appealing approach to many classical clustering problems. It stands out among standard methods as it enjoys the existence of a unique global optimal solution. Despite this advantage, convex clustering has not been widely adopted, due to its computationally intensive nature. To address this obstacle, especially in the "big data" setting, we introduce a Scalable cOnvex cLustering AlgoRithm via Parallel Coordinate Descent Method (SOLAR-PCDM) that improves the algorithm's scalability by combining a parallelizable algorithm with a compression strategy. This idea is in line with the rise and ever increasing availability of high performance computing systems built around multi-core processors, GPU-accelerators, and computer clusters. SOLAR-PCDM consists of two parts. In the first part, we develop a method called weighted convex clustering to recover the solution path by formulating a sequence of smaller equivalent optimization problems. In the second part, we utilize the Parallel Coordinate Descent Method (PCDM) to solve a specific convex clustering problem. We demonstrate the correctness and scalability of our algorithm on both simulated and real data examples.

关键词： Convex optimization Parallel computing Sparsity Unsupervised Learning

来源：评论

学校读者我要写书评

暂无评论

Adaptive multi-core Real- Time Scheduling Based on Reinforcement Learning

Adaptive Multi-Core Real- Time Scheduling Based on Reinforce...

引用

international Conference on Control and Automation (ICCA)

作者： Yonghui Liang Hui Li Fei Shen Qimin Xu Shuna Hua Shanying Zhu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Re-search Center of Intelligent Control and Management Shanghai China Key Laboratory of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China North Information Control Research Academy Group Company Ltd. Nanjing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

With the transformation towards industrial intel-ligence, multi-core processors are increasingly being applied in real-time networked control systems to ensure secure exe-cution of sensing, computing and actuating tasks under time constraints. However, existing scheduling methods result in either low CPU utilization or many missed task deadlines in dynamic systems. In this paper, we propose a two-layer scheduling architecture to address this issue by fully exploring the complex dependency between real-time tasks. To be specific, the local layer determines task execution priorities considering both dependency between tasks and deadline constraints by utilizing a reinforcement learning approach. Moreover, to better utilize the parallel capabilities of multi-core processors and reduce temporal collisions, this paper minimizes the requested core count for the task set based on a greedy strategy. The global layer designs a scheduling algorithm based on the pre-empt method and provides schedulability analysis of multiple task sets. Experimental results validate the correctness of the proposed scheduling approach, and efficiency is demonstrated through comparisons with baseline method.

关键词： Job shop scheduling multicore processing Scheduling algorithms Networked control systems Reinforcement learning Real-time systems Sensors

来源：评论

学校读者我要写书评

暂无评论

Practice and Experience in using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures

Practice and Experience in using Parallel and Scalable Machi...

引用

35th ieee international Parallel and Distributed Processing Symposium (IPDPS)

作者： Riedel, Morris Sedona, Rocco Barakat, Chadi Einarsson, Petur Hassanian, Reza Cavallaro, Gabriele Book, Matthias Neukirchen, Helmut Lintermann, Andreas Univ Iceland Dept Comp Sci Reykjavik Iceland Forschungszentrum Julich Julich Supercomp Ctr Julich Germany

ISBN: (纸本)9781665435772

We observe a continuously increased use of Deep Learning (DL) as a specific type of Machine Learning (ML) for data-intensive problems (i.e., 'big data') that requires powerful computing resources with equally increasing performance. Consequently, innovative heterogeneous High-Performance computing (HPC) systems based on multi-core CPUs and many-core GPUs require an architectural design that addresses end user communities' requirements that take advantage of ML and DL. Still the workloads of end user communities of the simulation sciences (e.g., using numerical methods based on known physical laws) needs to be equally supported in those architectures. This paper offers insights into the Modular Supercomputer Architecture (MSA) developed in the Dynamic Exascale Entry Platform (DEEP) series of projects to address the requirements of both simulation sciences and data-intensive sciences such as High Performance Data Analytics (HPDA). It shares insights into implementing the MSA in the Julich Supercomputing Centre (JSC) hosting Europe No. 1 Supercomputer Julich Wizard for European Leadership Science (JUWELS). We augment the technical findings with experience and lessons learned from two application communities case studies (i.e., remote sensing and health sciences) using the MSA with JUWELS and the DEEP systems in practice. Thus, the paper provides details into specific MSA design elements that enable significant performance improvements of ML and DL algorithms. While this paper focuses on MSA-based HPC systems and application experience, we are not losing sight of advances in Cloud computing (CC) and Quantum computing (QC) relevant for ML and DL.

关键词： High performance computing cloud computing quantum computing machine learning deep learning parallel and distributed algorithms remote sensing health sciences modular supercomputer architecture

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Azalea on many-core test bed system 12

Evaluation of Azalea on many-core test bed system

引用

12th international Conference on ICT Convergence (ICTC) - Beyond the Pandemic Era with ICT Convergence Innovation

作者： Jeong, Yeonjeong Kim, Jinmee Jeon, Seunghyub Cha, Seung-Jun Jung, Sungin Elect & Telecommun Res Inst ETRI Future Comp Res Div Daejeon South Korea

ISBN: (纸本)9781665423830

Recently, high-performance computing processors are changing to a many-core processor system environment. We approached the development of a unikernel based multi-kernel operating system, called Azalea for many-core system. In this paper, we develop a test bed system which can emulate 1K many-core system by combining several systems with NFS over RDMA on InfiniBand. And, we intend to evaluate the performance and scalability of Azalea on the many-core test bed system. It can be seen that the performance of AIM7 increases as the number of cores increases.

关键词： Azalea multi-kernel unikernel OS scalability

来源：评论

学校读者我要写书评

暂无评论

Is General Purpose Sensing a Pipe Dream? A Case Study in Ambient multi-sensing for Human Activity Recognition 1

Is General Purpose Sensing a Pipe Dream? A Case Study in Amb...

引用

First ACM international workshop on Cyber Physical Human System Design and Implementation

作者： Chowdhury, Tahiya Aldeer, Murtadha Yu, Justin Florentine, Joseph Haynes, Amber Ortiz, Jorge Rutgers State Univ ECE Dept New Brunswick NJ 08854 USA Rutgers State Univ WINLAB New Brunswick NJ USA Rutgers State Univ CS Dept New Brunswick NJ USA

ISBN: (纸本)9781450384407

Smart spaces equipped with sensors and combined with learning are becoming increasingly popular for many ubiquitous computing applications. However, application performance depends on many factors, including the number of sensors deployed, the phenomena they measure, their placement throughout the space, and spatio-temporal human-activity distribution characteristics. This work examines the sensitivity of activity-recognition models on the placement and distribution of multi-sensing measurement points in space. We present the results of an empirical study, whereby multi-sensing measurement units are placed throughout a room and train models to identify the type of human activity they observe. Our results show that while our models achieve 95% accuracy, performance degrades with distance and can be highly dependent on unanticipated sensor types. Certain phenomena trigger sensors that are difficult to anticipate a priori, supporting the notion that multi-sensing is useful for general activity recognition and improves robustness. We also show that the pattern of triggered sensors may not be consistent for the same event. Our results suggest designing more adaptive classification models and can guide the design of future cyber-physical systems to capture human activities.

关键词： Sensors multi-sensing Testbed Activity recognition

来源：评论

学校读者我要写书评

暂无评论

English-Chinese Translation Online Teaching System Based on Data Mining Algorithm 2

English-Chinese Translation Online Teaching System Based on ...

引用

2nd ieee international Conference on Advanced Technologies in Intelligent Control, Environment, computing and Communication Engineering, ICATIECE 2022

作者： Li, Chenxi Jilin University of Finance and Economics Department of Public Foreign Language Teaching and Research Changchun Jilin China International School of Chinese Studies Northeast Normal University Changchun Jilin China

ISBN: (纸本)9781665493963

With the rapid development of modern communication technology, mobile phones, as an indispensable communication tool for people, record the trajectory of people's activities, not only in the real space, but also in the network space. The analysis and mining of all kinds of information data has been very. Data mining, which plays a crucial role in many scenarios, can help us discover a lot of valuable knowledge and anomaly patterns. The cultivation of translation ability is the core goal of current translation teaching, and the research on the composition of translation ability and the methods to improve translation ability is increasingly becoming the focus of translation teaching research. The development of translation ability is a dynamic interactive process, not a linear process guided by gradual input, but a dyna mic systematic behavior full of peaks, valleys, advances, reversals, stagnation, and even leaps forward, since it is composed of multiple sub-Abilities and the multi-sub-Abilities do not develop synchronously. The characteristics of dynamic assessment coincide with the dynamic change and complexity of the development of translation ability. In this paper, data mining algorithms are used to study the existing English-Chinese translation online systems. © 2022 ieee.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Teaching PDC in the Time of COVID: Hands-on Materials for Remote Learning

Teaching PDC in the Time of COVID: Hands-on Materials for Re...

引用

35th ieee international Parallel and Distributed Processing Symposium (IPDPS)

作者： Adams, Joel C. Brown, Richard Matthews, Suzanne J. Shoop, Elizabeth Calvin Univ Grand Rapids MI 49546 USA St Olaf Coll Northfield MN 55057 USA US Mil Acad West Point NY 10996 USA Macalester Coll St Paul MN 55105 USA

ISBN: (纸本)9781665435772

In response to shifts in the hardware foundations of computing, parallel and distributed computing (PDC) is now a key piece of the core CS curriculum. For CS educators, the COVID-19 pandemic and the resulting switch to remote-learning add new challenges to the tasks of helping learners understand abstract PDC concepts and equipping them with hands-on practical skills. This paper presents several novel teaching materials for teaching PDC remotely, including: (i) using a Runestone Interactive "virtual" handout to learn how to run OpenMP multithreaded programs on a Raspberry Pi, and (ii) using Google Colab and Jupyter notebooks to run mpi4py instances on remote systems and thus learn about MPI distributed multiprocessing. The authors piloted these strategies during a multi-day faculty development workshop on teaching PDC. Assessment data indicates that the materials greatly aided professional development and preparedness to teach PDC.

关键词： Raspberry Pi Runestone Interactive Google Colab Remote Education Parallel & Distributed computing MPI OpenMP Python

来源：评论

学校读者我要写书评

暂无评论

multiLogVC: Efficient Out-of-core Graph Processing Framework for Flash Storage 35

MultiLogVC: Efficient Out-of-Core Graph Processing Framework...

引用

35th ieee international Parallel and Distributed Processing Symposium (IPDPS)

作者： Matam, Kiran Kumar Hashemi, Hanieh Annavaram, Murali Facebook Inc Menlo Pk CA 94025 USA Univ Southern Calif Elect Engn Dept Los Angeles CA 90007 USA

ISBN: (纸本)9781665440660

Graph analytics are at the heart of a broad range of applications such as drug discovery, page ranking, transportation systems, and recommendation models. When graph size exceeds the available memory size in a computing node, out-of-core graph processing is needed. For the widely used out-of-core graph processing systems. the graphs are stored and accessed from a long latency SSD storage, which becomes a significant performance bottleneck. To tackle this long latency this work exploits the key insight that that nearly all graph algorithms have a dynamically varying number of active vertices that must be processed in each iteration. However, existing graph processing frameworks, such as GraphChi, load the entire graph in each iteration even if a small fraction of the graph is active. This limitation is due to the structure of the graph storage used by these systems. In this work, we propose to use a compressed sparse row (CSR) based graph storage that is more amenable for selectively loading only a few active vertices in each iteration. However, CSR based graph processing suffers from random update propagation to many target vertices. To solve this challenge, we propose to use a multi-log update mechanism that logs updates separately, rather than directly update the active edges and vertices in a graph. The multi-log system maintains a separate log per each vertex interval (a group of vertices). This separation enables efficient processing of all updates bound to each vertex interval by just loading the corresponding log. Further, by logging all the updates associated with a vertex interval in one contiguous log this approach reduces read amplification since all the pages in the log will be processed in the next iteration without wasted page reads. Over the current state of the art out-of-core graph processing framework, our evaluation results show that the multiLogVC framework improves performance by up to 17.84x, 1.19x, 1.65x, 1.38x, 3.15x, and 6.00x for the widely

关键词： out-of-core graph processing graph analytics SSD storage systems log storage

来源：评论

学校读者我要写书评

暂无评论

Parasitic-Aware Modelling for Neural Networks Implemented with Memristor Crossbar Array 14

Parasitic-Aware Modelling for Neural Networks Implemented wi...

引用

14th ieee international Symposium on Embedded multicore/many-core systems-on-Chip (MCSoC)

作者： Cao, Tiancheng Liu, Chen Gao, Yuan Goh, Wang Ling Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore Agcy Sci Technol & Res Inst Microelect Singapore Singapore

ISBN: (纸本)9781665438605

This paper presents a parasitic-aware modelling approach called alpha beta-matrix model for the simulation of neural network (NN) implemented with memristor crossbar array. The line resistance, which is the key parasitic in a memristor crossbar array is analyzed and incorporated into the model. The proposed method estimates the line resistance IR drop with computation complexity of O (mn), in contrast to O(m(2)n(2)) required by the classical matrix based Kirchhoff's Current Law (KCL) equations solver. The impact of the crossbar array parasitics to the vector-matrix multiplication (VMM) computation and multi-layer NN classification accuracy are also analyzed. The advantages of the proposed parasitic-aware model are demonstrated through an example of 2-layer perceptron implemented with resistive random access memory (RRAM) crossbar array for MNIST written digits classification. 97.3% classification accuracy is achieved on 64x64 6-bit RRAM crossbar arrays. Compared to the KCL solver, the classification accuracy degradation is less than 0.4% with line resistance up to 4.5 Omega.

关键词： Analog computing memristor crossbar line resistance vector matrix multiplication

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98页 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：