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

9,285 篇 会议
365 篇 期刊文献
33 册 图书
1 篇 学位论文

馆藏范围

9,684 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,570 篇 工学
- 4,179 篇 计算机科学与技术...
- 2,156 篇 软件工程
- 849 篇 电气工程
- 638 篇 信息与通信工程
- 313 篇 控制科学与工程
- 227 篇 电子科学与技术（可...
- 83 篇 网络空间安全
- 65 篇 机械工程
- 56 篇 石油与天然气工程
- 55 篇 材料科学与工程（可...
- 52 篇 仪器科学与技术
- 50 篇 生物医学工程（可授...
- 40 篇 动力工程及工程热...
- 34 篇 生物工程
- 32 篇 建筑学
- 31 篇 安全科学与工程
- 29 篇 环境科学与工程（可...
- 28 篇 力学（可授工学、理...
- 27 篇 土木工程
- 26 篇 光学工程
1,073 篇 理学
- 862 篇 数学
- 129 篇 统计学（可授理学、...
- 125 篇 系统科学
- 101 篇 物理学
- 48 篇 生物学
- 34 篇 化学
808 篇 管理学
- 626 篇 管理科学与工程(可...
- 296 篇 工商管理
- 220 篇 图书情报与档案管...
71 篇 经济学
- 68 篇 应用经济学
22 篇 法学
22 篇 医学
18 篇 农学
16 篇 文学
10 篇 教育学
6 篇 军事学
1 篇 艺术学

主题

1,212 篇 distributed data...
993 篇 distributed comp...
954 篇 parallel process...
780 篇 concurrent compu...
779 篇 computer science
695 篇 databases
617 篇 computer archite...
586 篇 application soft...
553 篇 computational mo...
463 篇 parallel process...
369 篇 scalability
358 篇 distributed comp...
352 篇 distributed proc...
327 篇 hardware
325 篇 database systems
294 篇 processor schedu...
294 篇 costs
293 篇 parallel program...
291 篇 resource managem...
269 篇 fault tolerance

机构

32 篇 ibm thomas j. wa...
20 篇 school of comput...
19 篇 oak ridge natl l...
15 篇 college of compu...
13 篇 oak ridge nation...
13 篇 oak ridge nation...
13 篇 pacific northwes...
12 篇 iit dept comp sc...
12 篇 lawrence berkele...
12 篇 argonne national...
12 篇 mathematics and ...
11 篇 department of co...
11 篇 georgia institut...
11 篇 department of co...
11 篇 mathematics and ...
11 篇 department of co...
11 篇 department of co...
11 篇 lawrence berkele...
10 篇 school of comput...
10 篇 lawrence berkele...

作者

21 篇 a. choudhary
15 篇 boukerche azzedi...
13 篇 dongarra jack
13 篇 sun xian-he
11 篇 hoefler torsten
11 篇 s.k. das
11 篇 jack dongarra
11 篇 kurt rothermel
10 篇 choudhary a
9 篇 raicu ioan
9 篇 jun zhang
9 篇 m. takizawa
9 篇 yong chen
9 篇 ciprian dobre
9 篇 l.r. welch
9 篇 welch lonnie r.
9 篇 t. kurc
9 篇 chen haibo
9 篇 florin pop
9 篇 cameron kirk w.

语言

9,632 篇 英文
31 篇 其他
21 篇 中文

检索条件"任意字段=International Symposium on Databases in Parallel and Distributed Systems"

共 9684 条记录，以下是581-590 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：

Learning-Based Hierarchical Adaptive Congestion Control with Low Training Overhead

Learning-Based Hierarchical Adaptive Congestion Control with...

引用

international symposium on parallel and distributed Processing with Applications, ISPA

作者： Jinbin Hu Zikai Zhou Shuying Rao Yujie Peng Bowen Bao Chang Ruan Changsha University of Science and Technology ChangSha China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Most congestion control mechanisms perform well in specific network environments, but none can consistently deliver good performance across all scenarios. Recently proposed frameworks based on reinforcement learning can flexibly select congestion control algorithms to adapt to dynamic changes in network conditions. However, frequently altering the congestion control mechanisms during relatively stable periods of the network actually leads to instability and unnecessary computational overhead. In this paper, we propose a hierarchical adaptive congestion control algorithm (HACC) to be resilient to the varying network. HACC dynamically selects the appropriate congestion control mechanism only when the current congestion control algorithm is not suitable for the current network state, rather than changing the congestion control scheme every training cycle to ensure network stability. The simulation results show that under different realistic workloads, HACC significantly reduces the computational overhead and improves throughput. Specifically, HACC reduces average overhead by 31% and improves throughput by up to 47%, 35%, 23%, and 15% compared to Cubic, Reno, BBR, and Antelope, respectively.

关键词： Training distributed processing Protocols Adaptive systems Heuristic algorithms Simulation Telecommunication traffic Reinforcement learning Throughput Stability analysis

来源：评论

学校读者我要写书评

暂无评论

DUST: Resource-Aware Telemetry Offloading with A distributed Hardware-Agnostic Approach

DUST: Resource-Aware Telemetry Offloading with A Distributed...

引用

IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Mehrnaz Sharifian Diman Zad Tootaghaj Chen-Nee Chuah Puneet Sharma UC Davis Hewlett Packard Enterprise (Aruba Networks) Hewlett Packard Labs

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

In-device network monitoring has emerged as a promising alternative to centralized telemetry for gaining insights into the status and behavior of network devices. Despite its advantages of providing in-depth device telemetry and predicting failures in advance, it can impose substantial computational and storage burdens, potentially hindering networking devices' core switching and bridging functions. In light of this challenge, DUST system is introduced to dynamically distribute and offload in-device monitoring tasks by harnessing the available computational resources across network nodes. It is designed to be hardware-agnostic, making it deployable on switches, servers, DPUs, SmartNICs, and other relevant devices. Our initial experiments on a real data center testbed indicate that DUST can reduce CPU utilization by up to 50% and memory usage by up to 15% in the context of in-device monitoring workloads. We present a comprehensive system architecture that encompasses various nodes and discuss the flow of packets and message communications. To tackle one of the primary challenges posed by DUST-namely, the optimal relocation of computations while considering network performance constraints and controllable routing decisions-we mathematically formulate the problem as an Integer Linear Program (ILP), along with a heuristic algorithm to reduce the computational complexity. We thoroughly examine the effectiveness and scalability aspects of our algorithms by considering various network sizes and use cases.

关键词： distributed processing Scalability Heuristic algorithms systems architecture Switches Routing Telemetry

来源：评论

学校读者我要写书评

暂无评论

Capturing Periodic I/O Using Frequency Techniques

Capturing Periodic I/O Using Frequency Techniques

引用

international symposium on parallel and distributed Processing (IPDPS)

作者： Ahmad Tarraf Alexis Bandet Francieli Boito Guillaume Pallez Felix Wolf Department of Computer Science Technical University of Darmstadt Darmstadt Germany Inria LaBRI UMR 5800 Univ. Bordeaux CNRS Bordeaux INP Talence France Inria Rennes France

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

Many HPC applications perform their I/O in bursts that follow a periodic pattern. This allows for making predictions as to when a burst occurs. System providers can take advantage of such knowledge to reduce file-system contention by actively scheduling I/O bandwidth. The effectiveness of this approach, however, depends on the ability to detect and quantify the periodicity of I/O patterns online. In this paper, we introduce FTIO, an online method to detect periodic I/O phases, which is based on discrete Fourier transform (DFT), combined with outlier detection. We provide metrics that gauge the confidence in the output and tell how far from being periodic the signal is. We validate our approach with large-scale experiments on a production system and examine its limitations extensively. Our experiments show that FTIO has a mean error below 11%. Finally, we demonstrate that FTIO allowed the I/O scheduler Set10 to boost system utilization by 26% and reduce I/O slowdown by 56%.

关键词： Measurement Wavelet transforms Production systems distributed processing Discrete Fourier transforms Merging Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Turbo Table: A Semantic-Aware Cache Acceleration System

Turbo Table: A Semantic-Aware Cache Acceleration System

引用

international symposium on parallel and distributed Processing with Applications, ISPA

作者： Hao Yuan Chentao Wu Jie Li Minyi Guo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

In the current storage disaggregation architecture, the challenge of quickly retrieving data from storage clusters is typically addressed using caching or data pushdown strategies to accelerate data access and reduce data movement. However, most caching systems still manage data at the page granularity level. For compute-intensive applications, such as analytical applications, this coarse data management approach leads to underutilized computational resources and read-write amplification issues. Additionally, insufficient cache utilization results in inefficient data flow. By managing data at the schema granularity level and modifying the data flow path, we alleviate the read-write amplification problem and improve data transfer speeds. Managing data at the schema level also enables semantic awareness, allowing us to proactively analyze semantics for more precise cache management strategies and accurate prefetching, rather than passively waiting for cache request sequences. We also observed that native compute caches waste valuable cache space and complicate the association between original and result data. To address this, we propose a multi-grained caching model to avoid these limitations. Compared to the baseline, Turbo Table reduces computation time by 2.4% to 36.8%.

关键词： distributed processing Accuracy Prefetching Computational modeling Semantics Computer architecture Data transfer

来源：评论

学校读者我要写书评

暂无评论

High-Performance Computing for Efficient Transaction Processing: A Comparative Study of parallel and Sequential Execution using SQLite

High-Performance Computing for Efficient Transaction Process...

引用

IoT Based Control Networks and Intelligent systems (ICICNIS), international Conference on

作者： C.V.Roshan Balaji Shaman. KR V.Pritham Raj N.Nithish Kumar Kumaran K School of Computer Science and Engineering Vellore Institute of Technology Chennai campus India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

High-performance computing (HPC) has become an essential tool for improving the efficiency and scalability of transaction processing systems, especially as data volumes continue to grow in fields like finance, e-commerce, and blockchain. This paper presents a comparative study of parallel and sequential transaction processing methods using an SQLite database. Specifically, the research investigates the impact of HPC techniques on transaction throughput, processing speed, and efficiency by simulating 1,000 user transactions. The study employs Python's multiprocessing module to simulate parallel execution, contrasting it with traditional sequential execution. Key performance indicators, including execution time, transaction success rate, and system efficiency, were analyzed to determine the advantages of parallel processing in a transaction-heavy environment. Our results reveal that parallel execution significantly reduces processing time, boosts throughput, and increases overall system efficiency compared to sequential processing. Additionally, the study discusses how parallel processing techniques can address common bottlenecks in transaction-heavy applications and provide solutions for improving the performance of large-scale, data-intensive systems. The findings demonstrate the potential for using HPC to optimize database operations, particularly in systems where high-volume transaction processing is a critical requirement. Future work will explore advanced parallelization strategies, fault tolerance mechanisms, and integrations with distributed databases and blockchain systems. This research contributes to the growing body of knowledge on optimizing transaction processing in high-performance computing environments, with potential applications across various sectors, including financial services, e-commerce, and blockchain technology.

关键词： High performance computing Scalability Key performance indicator Process control parallel processing Throughput Blockchains Electronic commerce Resource management Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

Tackling Cold Start in Serverless Computing with Multi-Level Container Reuse

Tackling Cold Start in Serverless Computing with Multi-Level...

引用

international symposium on parallel and distributed Processing (IPDPS)

作者： Amelie Chi Zhou Rongzheng Huang Zhoubin Ke Yusen Li Yi Wang Rui Mao Hong Kong Baptist University Nankai University Guangdong Provincial Key Lab of Popular High Performance Computers Shenzhen University

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

In Serverless Computing, function cold-start is a major issue that causes delay of the system. Various solutions have been proposed to address function cold-start issue, among which keeping containers alive after function completion is an easy and commonly adopted way in real serverless clouds. However, when reusing warm containers for function warm starts, existing systems only match functions to containers with the same configurations. This greatly limits the warm resource utilization. Our analysis of real-world applications reveals that many serverless applications share the same operating system and language frameworks. Thus, we propose multi-level container reuse that tries to reduce the startup latency of functions using "similar" containers to greatly improve warm resource utilization. Due to the complexity of selecting the best container reuse solutions, we designed a Deep Reinforcement Learning (DRL) based scheduler to efficiently and effectively address the problem. Moreover, we released a new serverless benchmark named FStartBench that contains detailed package information for comparing the effectiveness of different function cold-start methods. Experiments based on FStartBench show that, given a warm resource pool with fixed size, our DRL-based scheduler can achieve up to 53% reduction on the average function startup latency compared to state-of-the-art solutions.

关键词： distributed processing Operating systems Serverless computing Containers Benchmark testing Deep reinforcement learning Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Efficient erasure-coded multi-data block update methods for heterogeneous storage environments

Efficient erasure-coded multi-data block update methods for ...

引用

international symposium on parallel and distributed Processing with Applications, ISPA

作者： Hengyu Wang Bing Wei Ning Luo Qian Chen Yi Wu Shudong Zhang Lijuan Zhou School of Cyberspace Security Hainan University Hainan China School of International Communication and Arts Hainan University Hainan China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Erasure-coded storage systems can achieve highly reliable data storage with low storage overhead. However, updating data blocks necessitates updating parity blocks, and updating multiple data blocks incurs heavy I/O and computational overhead, leading to prolonged update times in heterogeneous storage environments. This paper proposes an erasure-coded multi-data block update method for heterogeneous storage environments, named MBUS, to expedite data updates. MBUS blends re-encoding and delta-based updates and considers factors such as intermediate blocks, computational overhead, and I/O overhead across different storage media. It iteratively computes the minimal I/O time for updating each parity block dynamically. Once the computation equation for each parity block is determined, MBUS prioritizes computing common XOR expressions and reuses the results to reduce the number of XOR operations. MBUS caches a certain number of scheduling plans to minimize redundant computations in subsequent updates, thereby reducing computation time. Experimental results replaying real-world traces demonstrate that MBUS reduces update time by 64.43% compared to state-of-the-art techniques.

关键词： distributed processing Processor scheduling Memory Media Mathematical models Reliability Optimization

来源：评论

学校读者我要写书评

暂无评论

UnifyFS: A User-level Shared File System for Unified Access to distributed Local Storage

UnifyFS: A User-level Shared File System for Unified Access ...

引用

international symposium on parallel and distributed Processing (IPDPS)

作者： Michael J. Brim Adam T. Moody Seung-Hwan Lim Ross Miller Swen Boehm Cameron Stanavige Kathryn M. Mohror Sarp Oral Oak Ridge National Laboratory USA Lawrence Livermore National Laboratory USA

We introduce UnifyFS, a user-level file system that aggregates node-local storage tiers available on high performance computing (HPC) systems and makes them available to HPC applications under a unified namespace. UnifyFS employs transparent I/O interception, so it does not require changes to application code and is compatible with commonly used HPC I/O libraries. The design of UnifyFS supports the predominant HPC I/O workloads and is optimized for bulk-synchronous I/O patterns. Furthermore, UnifyFS provides customizable file system semantics to flexibly adapt its behavior for diverse I/O workloads and storage devices. In this paper, we discuss the unique design goals and architecture of UnifyFS and evaluate its performance on a leadership-class HPC system. In our experimental results, we demonstrate that UnifyFS exhibits excellent scaling performance for write operations and can improve the performance of application checkpoint operations by as much as 3× versus a tuned configuration.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Energy Optimization through a Multidimensional distributed Scheduling Approach

Energy Optimization through a Multidimensional Distributed S...

引用

international symposium on parallel and distributed Computing

作者： Humberto Valera Leonel Isaac Guerrero Giraldo Carlos Alejandro Sivira Mu˜Noz Alan Alfredo Rojas Marroquin Lucas Aguilar Damas Marc Dalmau Philippe Roose Yudith Cardinale Technopôle DOMOLANDES Saint-Geours-de-Maremne France Universidad Simón Bolivar Caracas Venezuela Universidad Católica San Pablo Arequipa Peru Universidad Internacional de Valencia Spain E2S UPPA University of Pau Anglet France

ISBN: (数字)9798350369199

ISBN: (纸本)9798350369205

distributed systems, spanning pervasive, cloud, and edge computing, require robust scheduling for tasks and data management, facing challenges like hardware diversity, QoS, localization, and energy efficiency. Current solutions often lack a comprehensive approach, failing to achieve balanced load management, QoS, and notably in minimizing application energy use, a key modern concern. We propose a distributed scheduler using multidimensional spaces and data structures aimed at comprehensive load balancing, energy efficiency, and QoS. The scheduler indexes devices within the structure based on diverse criteria such as hardware availability, GPS, and energy features. It then organizes applications into abstract graphs, where nodes are containers and their data items (units of data accessed by the containers), and edges are the transfer rates among them. To migrate containers, the scheduler performs range queries within the structure for optimal devices. To organize data items, it finds the barycenter of the devices executing the containers linked to them. We evaluated our scheduler’s effectiveness using the PISCO simulator, comparing it against other energy-efficient schedulers.

关键词： Performance evaluation Location awareness Processor scheduling Quality of service Containers Load management Energy efficiency Scheduling Hardware Optimization

来源：评论

学校读者我要写书评

暂无评论

distributed On-Demand Deployment for Transparent Access to 5G Edge Computing Services

Distributed On-Demand Deployment for Transparent Access to 5...

引用

IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Josef Hammer Hermann Hellwagner Institute of Information Technology Alpen-Adria-Universität Klagenfurt Austria

Multi-access Edge Computing (MEC) is a central piece of 5G telecommunication systems and is essential to satisfy the challenging low-latency demands of future applications. MEC provides a cloud computing platform at the edge of the radio access network. Our previous publications argue that edge computing should be transparent to clients, leveraging Software-Defined Networking (SDN). While we introduced a solution to implement such a transparent approach, one question remained: How to handle user requests to a service that is not yet running in a nearby edge cluster? One advantage of the transparent edge is that one could process the initial request in the cloud. However, this paper argues that on-demand deployment might be fast enough for many services, even for the first request. We present an SDN controller that automatically deploys an application container in a nearby edge cluster if no instance is running yet. In the meantime, the user’s request is forwarded to another (nearby) edge cluster or kept waiting to be forwarded immediately to the newly instantiated instance. Our performance evaluations on a real edge/fog testbed show that the waiting time for the initial request – e.g., for annginx-based service – can be as low as 0.5 seconds – satisfactory for many applications.

关键词：

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 << < 55 56 57 58 59 60 61 62 63 64 > >>

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：