Cellular automata approach to scheduling problem

A. Swiecicka, F. Seredyński
{"title":"Cellular automata approach to scheduling problem","authors":"A. Swiecicka, F. Seredyński","doi":"10.1109/PCEE.2000.873596","DOIUrl":null,"url":null,"abstract":"In the paper we propose using cellular automata (CAs) to solve a problem of scheduling tasks of a parallel program in the two processor system. We examine a hypothesis that a nonlinear structure of a program graph can be approximated by a linear CA structure. Corresponding CAs solving the scheduling problem act according to some rules which must be found. Searching effective rules is conducted with the use of a genetic algorithm (GA). We show that for any initial allocation of tasks, a CA with discovered rules is able to find optimal or near-optimal solutions. Corresponding architecture of a CA is simpler than the ones known in the literature.","PeriodicalId":369394,"journal":{"name":"Proceedings International Conference on Parallel Computing in Electrical Engineering. PARELEC 2000","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings International Conference on Parallel Computing in Electrical Engineering. PARELEC 2000","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCEE.2000.873596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

Abstract

In the paper we propose using cellular automata (CAs) to solve a problem of scheduling tasks of a parallel program in the two processor system. We examine a hypothesis that a nonlinear structure of a program graph can be approximated by a linear CA structure. Corresponding CAs solving the scheduling problem act according to some rules which must be found. Searching effective rules is conducted with the use of a genetic algorithm (GA). We show that for any initial allocation of tasks, a CA with discovered rules is able to find optimal or near-optimal solutions. Corresponding architecture of a CA is simpler than the ones known in the literature.
元胞自动机方法求解调度问题
本文提出用元胞自动机来解决双处理机系统中并行程序的任务调度问题。我们检验了程序图的非线性结构可以用线性CA结构近似的假设。求解调度问题的相应ca遵循一定的规则,必须找到这些规则。利用遗传算法(GA)搜索有效规则。我们表明,对于任何任务的初始分配,具有已发现规则的CA能够找到最优或接近最优的解决方案。CA的相应架构比文献中已知的架构更简单。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信