仓库级计算机作业调度的基本原理及分析综述

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Kevin Exton, Maria Rodriguez Read
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引用次数: 0

摘要

在过去的十年中,对能够处理大型(仓库)规模计算机上异构工作负载需求的高效调度算法的研究已经达到了狂热的速度。从相关基础理论的基本结果出发,重点研究了仓库级计算机上高度并行作业的调度技术。本调查的目的是将文献中不同的调度思想和方法联系在一个松散的数学结果框架下,可以用来比较表面上不同的调度方法在一个共同的目标下。由于数学问题一般是np困难的,我们不强调严格的数学证明,相反,我们提倡使用数学结果来指导直觉。我们为读者提供了一些基本的工具,用于引导围绕分布式应用程序的作业调度的零散研究。我们还强调了文献中对基础理论的一些常见误解,这些误解会扭曲结果并可能限制研究进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Fundamental Principles and Analysis for Job Scheduling on Warehouse-Scale Computers
Over the last ten years, the search for efficient scheduling algorithms that can cope with heterogeneous workload demands on large (warehouse) scale computers has reached a feverish tempo. We focus on examining scheduling techniques for highly parallelizable jobs on warehouse-scale computers through the lens of basic results in relevant fundamental theories. The objective of this survey is to connect the disparate scheduling ideas and approaches in the literature under a loose framework of mathematical results that can be used to compare superficially different scheduling methodologies under a common goal. As the mathematical problem is NP-Hard in general, we do not emphasize rigorous mathematical proof, rather, we advocate for the use of mathematical results to guide intuition. We provide readers with some basic tools to use in navigating the fragmented research around job scheduling for distributed applications. We also highlight some common misunderstandings of fundamental theory in the literature that are skewing results and may be limiting research progress.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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