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

883 篇 会议
47 篇 期刊文献
12 册 图书
3 篇 学位论文

馆藏范围

945 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

414 篇 工学
- 397 篇 计算机科学与技术...
- 165 篇 软件工程
- 59 篇 电气工程
- 40 篇 信息与通信工程
- 30 篇 控制科学与工程
- 12 篇 动力工程及工程热...
- 9 篇 电子科学与技术（可...
- 9 篇 建筑学
- 9 篇 环境科学与工程（可...
- 8 篇 机械工程
- 4 篇 土木工程
- 3 篇 航空宇航科学与技...
- 3 篇 生物工程
- 2 篇 仪器科学与技术
- 2 篇 网络空间安全
152 篇 管理学
- 146 篇 管理科学与工程(可...
- 108 篇 工商管理
- 15 篇 图书情报与档案管...
59 篇 理学
- 41 篇 数学
- 10 篇 系统科学
- 7 篇 物理学
- 4 篇 生物学
- 4 篇 统计学（可授理学、...
12 篇 经济学
- 11 篇 应用经济学
- 1 篇 理论经济学
4 篇 法学
- 3 篇 社会学
- 1 篇 法学
2 篇 艺术学
- 2 篇 设计学（可授艺术学...
1 篇 教育学
- 1 篇 教育学
1 篇 文学
- 1 篇 新闻传播学

主题

428 篇 resource managem...
229 篇 processor schedu...
111 篇 grid computing
107 篇 scheduling
95 篇 dynamic scheduli...
93 篇 distributed comp...
66 篇 computational mo...
65 篇 scheduling algor...
62 篇 computer science
55 篇 parallel process...
54 篇 computer archite...
53 篇 quality of servi...
49 篇 concurrent compu...
49 篇 large-scale syst...
48 篇 application soft...
44 篇 operating system...
44 篇 real time system...
43 篇 load management
40 篇 runtime
38 篇 cloud computing

机构

5 篇 inria
5 篇 department of co...
5 篇 colorado state u...
4 篇 school of comput...
4 篇 university of ch...
4 篇 tadaam team inri...
3 篇 college of compu...
3 篇 lawrence livermo...
3 篇 colorado state u...
3 篇 univ chicago dep...
3 篇 lawrence livermo...
3 篇 grid computing a...
3 篇 high performance...
3 篇 computer enginee...
3 篇 tech univ munich...
3 篇 university of cr...
3 篇 national laborat...
3 篇 institute of com...
3 篇 aristotle univ t...
2 篇 sun microsystems...

作者

6 篇 rajkumar buyya
6 篇 siegel howard ja...
5 篇 h.j. siegel
5 篇 maciejewski anth...
5 篇 buyya rajkumar
5 篇 t. kidd
5 篇 albert y. zomaya
4 篇 d.p. spooner
4 篇 s.a. jarvis
4 篇 carmen carrión
4 篇 koenig gregory a...
4 篇 g.r. nudd
4 篇 blanca caminero
4 篇 r. buyya
4 篇 nudd gr
4 篇 wentong cai
4 篇 trystram denis
4 篇 chen yong
4 篇 elmroth erik
4 篇 g. manimaran

语言

939 篇 英文
5 篇 其他

检索条件"任意字段=International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems"

共 945 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：

scheduling Big Machine Learning Tasks on Clusters of Heterogeneous Edge Devices

Scheduling Big Machine Learning Tasks on Clusters of Heterog...

引用

international Communication systems and Networks and workshops, COMSNETS

作者： Saumya Mathkar Shreya Aiyer Yashovardhan Bapat Pinki Pinki Arnab K. Paul Vinayak Naik Department of CSIS BITS Pilani Goa India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Edge Computing has transformed machine learning by using computing closer to the data sources, thereby reducing latency. The ever-increasing volume of data has necessitated forming clusters of edge devices, possibly with heterogeneous capabilities. Managing heterogeneous resources such as computation and memory remains challenging. Given the capabilities of the edge devices, we need a simple technique suitable for an Edge Computing *** introduce a scheduling mechanism that leverages Integer Linear Programming (ILP) to optimize the overall computation time of ML-based tasks. We implement our scheduling mechanism that efficiently allocates resources, ensuring tasks are executed parallel across the cores of edge devices in a cluster by minimizing computation time. For tasks large enough to fit on any core, we leverage distributed learning to train the model in pieces and later combine them. We employ our ILP-based scheduler for efficient task allocation and compare its performance with a Greedy, simple approach based on best-fit technique. We evaluate our approach on three cases of sets of tasks on the spectrum of uniformity and size. Our results demonstrate two times the speed gain for our ILP-based approach over Greedy for the category with the least uniformity and large size.

关键词： Performance evaluation Computer aided instruction Machine learning algorithms Processor scheduling Distance learning Soft sensors Machine learning Integer linear programming resource management Edge computing

来源：评论

学校读者我要写书评

暂无评论

Performance Models of Data parallel DAG Workflows for Large Scale Data Analytics 37

Performance Models of Data Parallel DAG Workflows for Large ...

引用

37th IEEE international Conference on Data Engineering (IEEE ICDE)

作者： Shi, Juwei Lu, Jiaheng Microsoft Cooperat STCA Redmond WA 98052 USA Univ Helsinki Dept Comp Sci Helsinki Finland

ISBN: (纸本)9781665448901

Directed Acyclic Graph (DAG) workflows are widely used for large-scale data analytics in cluster-based distributed computing systems. Building an accurate performance model for a DAG on data-parallel frameworks (e.g., MapReduce) is critical to implement autonomic self-management big data systems. An accurate performance model is challenging because the allocation of pre-emptable system resources among parallel jobs may dynamically vary during execution. This resource allocation variation during execution makes it difficult to accurately estimate the execution time. In this paper, we tackle this challenge by proposing a new cost model, called Bottleneck Oriented Estimation (BOE), to estimate the allocation of preemptable resources by identifying the bottleneck to accurately predict task execution time. For a DAG workflow, we propose a state-based approach to iteratively use the resource allocation property among stages to estimate the overall execution plan. Extensive experiments were performed to validate these cost models with HiBench and TPC-H workloads. The BOE model outperforms the state-of-the-art models by a factor of five for task execution time estimation.

关键词： Data Analytics

来源：评论

学校读者我要写书评

暂无评论

4th workshop on parallel AI and systems for the Edge

4th Workshop on Parallel AI and Systems for the Edge

引用

IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

来源：评论

学校读者我要写书评

暂无评论

workshop on resource Arbitration for Dynamic Runtimes (RADR)

Workshop on Resource Arbitration for Dynamic Runtimes (RADR)

引用

IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

作者： Pete Beckman Emmanuel Jeannot Swann Perarnau Argonne National Laboratory Northwestern University Argonne IL USA TADaaM Team Inria Talence France Argonne National Laboratory Argonne IL USA

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

The question of efficient dynamic allocation of compute-node resources, such as cores, by independent libraries or runtime systems can be a nightmare. Scientists writing application components have no way to efficiently specify and compose resource-hungry components. As application software stacks become deeper and the interaction of multiple runtime layers compete for resources from the operating system, it has become clear that intelligent cooperation is needed. resources such as compute cores, in-package memory, and even electrical power must be orchestrated dynamically across application components, with the ability to query each other and respond appropriately. A more integrated solution would reduce intra-application resource competition and improve performance. Furthermore, application runtime systems could request and allocate specific hardware assets and adjust runtime tuning parameters up and down the software stack. The goal of this workshop is to gather and share the latest scholarly research from the community working on these issues, at all levels of the HPC software stack. This includes thread allocation, resource arbitration and management, containers, and so on, from runtime-system designers to compilers. We will also use panel sessions and keynote talks to discuss these issues, share visions, and present solutions.

关键词： distributed processing Runtime Conferences Operating systems Instruction sets Dynamic scheduling Libraries

来源：评论

学校读者我要写书评

暂无评论

Performance-Cost Optimization of Moldable Scientific Workflows 24th

Performance-Cost Optimization of Moldable Scientific Workflo...

引用

24th international workshop on Job scheduling Strategies for parallel Processing (JSSPP)

作者： Jaros, Marta Jaros, Jiri Brno Univ Technol Fac Informat Technol Ctr Excellence IT4Innovat Brno Czech Republic

ISBN: (纸本)9783030882242;9783030882235

Moldable scientific workflows represent a special class of scientific workflows where the tasks are written as distributed programs being able to exploit various amounts of computer resources. However, current cluster job schedulers require the user to specify the amount of resources per task manually. This often leads to suboptimal execution time and related cost of the whole workflow execution since many users have only limited experience and knowledge of the parallel efficiency and scaling. This paper proposes several mechanisms to automatically optimize the execution parameters of moldable workflows using genetic algorithms. The paper introduces a local optimization of workflow tasks, a global optimization of the workflow on systems with on-demand resource allocation, and a global optimization for systems with static resource allocation. Several objectives including the workflow makespan, computational cost and the percentage of idling nodes are investigated together with a trade-off parameter putting stress on one objective or another. The paper also discusses the structure and quality of several evolved workflow schedules and the possible reduction in makespan or cost. Finally, the computational requirements of evolutionary process together with the recommended genetic algorithm settings are investigated. The most complex workflows may be evolved in less than two minutes using the global optimization while in only 14s using the local optimization.

关键词： Task graph scheduling Workflow Genetic algorithm Moldable tasks Makespan estimation

来源：评论

学校读者我要写书评

暂无评论

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis

Generic and ML Workloads in an HPC Datacenter: Node Energy, ...

引用

international Conference on parallel and distributed systems (ICPADS)

作者： Xiaoyu Chu Daniel Hofstätter Shashikant Ilager Sacheendra Talluri Duncan Kampert Damian Podareanu Dmitry Duplyakin Ivona Brandic Alexandru Iosup Vrije Universiteit Amsterdam the Netherlands TU Wien Vienna Austria SURF Amsterdam the Netherlands National Renewable Energy Laboratory Colorado USA

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting science, business, and other decision-making processes. However, understanding how ML jobs impact the operation of HPC datacenters, relative to generic jobs, remains desirable but understudied. In this work, we leverage long-term operational data, collected from a national-scale production HPC datacenter, and statistically compare how ML and generic jobs can impact the performance, failures, resource utilization, and energy consumption of HPC datacenters. Our study provides key insights, e.g., ML-related power usage causes GPU nodes to run into temperature limitations, median/mean runtime and failure rates are higher for ML jobs than for generic jobs, both ML and generic jobs exhibit highly variable arrival processes and resource demands, significant amounts of energy are spent on unsuccessfully terminating jobs, and concurrent jobs tend to terminate in the same state. We open-source our cleaned-up data traces on Zenodo (https://doi. org/10.5281/zenodo.13685426), and provide our analysis toolkit as software hosted on GitHub (https://***/atlarge-research/2024-icpads-hpc-workload-characterization). This study offers multiple benefits for data center administrators, who can improve operational efficiency, and for researchers, who can further improve system designs, scheduling techniques, etc.

关键词： Measurement Energy consumption Runtime Graphics processing units Production Machine learning Software resource management System analysis and design Software development management

来源：评论

学校读者我要写书评

暂无评论

Online Analytics with Local Operator Rebinding for Simulation Data Stream Processing

Online Analytics with Local Operator Rebinding for Simulatio...

引用

international workshop/Symposium on distributed Simulation and Real-Time Applications (DS-RT)

作者： Xiaorui Du Andrea Piccione Adriano Pimpini Stefano Bortoli Alessandro Pellegrini Alois Knoll Technical University of Munich Huawei Munich Research Center Sapienza University of Rome Tor Vergata University of Rome

ISBN: (数字)9798331527211

ISBN: (纸本)9798331527228

Leveraging multiple threads to process high volumes of simulation data is a prevalent strategy in modern streaming data processing systems. Statically binding operators to specific threads is the most common design employed due to its simplicity in implementation and initial system configuration. However, this approach often fails to effectively account for the inherently dynamic nature of simulation data, potentially leading to inefficient resource utilisation and processing bottlenecks. To address these limitations, we present a novel mechanism for stream-processing operator rebinding that enables lock-free, dynamic workload rebalancing between worker threads. The rebinding is driven by an autonomic policy that captures workload imbalance in the stream-processing pipeline when multiple queries are computed and reacts to it by moving computation around the different threads. We evaluate our proposal using data generated from large-scale traffic simulations on which multiple queries are executed. The volume and organisation of the data we feed to the stream-processing pipeline significantly change over time, providing excellent grounds to evaluate our rebinding policy. The evaluation confirms that the performance of stream processing pipelines can be greatly improved using local operator rebinding.

关键词： Instruction sets Heuristic algorithms Pipelines Traffic control Dynamic scheduling Data processing Throughput Real-time systems resource management Proposals

来源：评论

学校读者我要写书评

暂无评论

When Less is More: Achieving Faster Convergence in distributed Edge Machine Learning

When Less is More: Achieving Faster Convergence in Distribut...

引用

international Conference on High Performance Computing

作者： Advik Raj Basani Siddharth Chaitra Vivek Advaith Krishna Arnab K. Paul Department of Computer Science and Information Systems DaSHLab BITS Pilani India

ISBN: (数字)9798331509095

ISBN: (纸本)9798331509101

distributed Machine Learning (DML) on resource-constrained edge devices holds immense potential for real-world applications. However, achieving fast convergence in DML in these heterogeneous environments remains a significant challenge. Traditional frameworks like Bulk Synchronous parallel (BSP) and Asynchronous Stochastic parallel (ASP) rely on frequent, small updates that incur substantial communication overhead and hinder convergence speed. Furthermore, these frameworks often employ static dataset sizes, neglecting the heterogeneity of edge devices and potentially leading to straggler nodes that slow down the entire training process. The straggler nodes, i.e., edge devices that take significantly longer to process their assigned data chunk - hinder the overall training speed. To address these limitations, this paper proposes Hermes, a novel probabilistic framework for efficient DML on edge devices. This framework leverages a dynamic threshold based on recent test loss behavior to identify statistically significant improvements in the model's generalization capability, hence transmitting updates only when major improvements are detected, thereby significantly reducing communication overhead. Additionally, Hermes employs dynamic dataset allocation to optimize resource utilization and prevents performance degradation caused by straggler nodes. Our evaluations on a real-world heterogeneous resource-constrained environment demonstrate that Hermes achieves faster convergence compared to state-of-the-art methods, resulting in a remarkable 13.22x reduction in training time and a 62.1% decrease in communication overhead.

关键词： Training Performance evaluation Accuracy Stochastic processes Machine learning Dynamic scheduling Propagation losses Probabilistic logic resource management Convergence

来源：评论

学校读者我要写书评

暂无评论

A Mathematical Framework for Optimizing Lexical Analysis on Multi-Core Architectures

A Mathematical Framework for Optimizing Lexical Analysis on ...

引用

Sustainable Expert systems (ICSES), international Conference on

作者： Vaikunta Pai T Priyadarshini P B Sunil Kamath Shreyas Vivek Manjunatha Nethravathi P S Department of ISE NITTE (Deemed to be University) NMAM Institute of Technology (NMAMIT) Nitte India Department of Computer Applications St Joseph Engineering College Mangaluru India School of Information Technology Deakin University Waurn Ponds VIC Australia Department of CSE Manipal Institute of Technology Manipal Academy of Higher Education (MAHE) Manipal India Department of CSE Shree Devi Institute of Technology Mangaluru India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

In the field of multi-core computing systems, optimizing the distribution of tasks across multiple cores is essential to harness maximum performance potential. Traditional static task allocation methods, often employed in lexical analysis-the initial and vital phase of compiling and interpreting source code-frequently result in imbalanced workloads and suboptimal resource utilization. This paper introduces an innovative and sophisticated mathematical model for dynamic task allocation specifically tailored to lexical analysis, aiming to revolutionize how tasks are distributed across multiple cores. By employing advanced dynamic allocation techniques, our proposed model not only ensures balanced workload distribution but also scales efficiently with varying computational demands. This novel approach significantly enhances the efficiency of lexical analysis in multi-core environments, leading to substantial improvements in processing times and resource utilization. Extensive experimental results validate the superiority of our method, showcasing dramatic reductions in processing latency and a more effective exploitation of multi-core capabilities. This dynamic model not only advances the field of lexical analysis but also sets a new benchmark for task allocation strategies in multi-core computing systems, promising broader applicability and future innovations in compiler design and resource management.

关键词： Adaptation models Analytical models Multicore processing Computational modeling Scalability parallel processing Dynamic scheduling Mathematical models Computational efficiency resource management

来源：评论

学校读者我要写书评

暂无评论

Plan-Based Job scheduling for Supercomputers with Shared Burst Buffers 27th

Plan-Based Job Scheduling for Supercomputers with Shared Bur...

引用

27th international European Conference on parallel and distributed Computing (Euro-Par)

作者： Kopanski, Jan Rzadca, Krzysztof Univ Warsaw Inst Informat Stefana Banacha 2 PL-02097 Warsaw Poland

ISBN: (纸本)9783030856656;9783030856649

The ever-increasing gap between compute and I/O performance in HPC platforms, together with the development of novel NVMe storage devices (NVRAM), led to the emergence of the burst buffer concept an intermediate persistent storage layer logically positioned between random-access main memory and a parallel file system. Despite the development of real-world architectures as well as research concepts, resource and job management systems, such as Slurm, provide only marginal support for scheduling jobs with burst buffer requirements, in particular ignoring burst buffers when backfilling. We investigate the impact of burst buffer reservations on the overall efficiency of online job scheduling for common algorithms: First-Come-First-Served (FCFS) and Shortest-Job-First (SJF) EASY-backfilling. We evaluate the algorithms in a detailed simulation with I/O side effects. Our results indicate that the lack of burst buffer reservations in backfilling may significantly deteriorate scheduling. We also show that these algorithms can be easily extended to support burst buffers. Finally, we propose a burst-buffer-aware plan-based scheduling algorithm with simulated annealing optimisation, which improves the mean waiting time by over 20% and mean bounded slowdown by 27% compared to the burst-buffer-aware SJF-EASY-backfilling.

关键词： High performance computing (HPC) EASY backfilling Online job scheduling Multi-resource scheduling Simulated annealing Nonvolatile memory Simulation

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95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：