Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 3
763-767

On-line prediction of application runtime using schedule historical data

Xu Lunfan
Xiong Min
Xiao Yonghao
Institute of Computer Application, China Academy of Engineering Physics, Mianyang Sichuan 621900, China
DOI: 10.19734/j.issn.1001-3695.2018.08.0624

Abstract

Traditional runtimes based on user estimating is usually less accurate. This paper combined the categorization with the instance-based learning method, used the template similarity and numerical similarity method to find the similar jobs of the current jobs in historical data, and used historical scheduling data to predict the runtimes of the current jobs. This paper only took seven job attributes into account, which included user name, group name, queue name, application name, requested number of processors, requested runtime, requested memory. It applied genetic algorithm to train the best parameters, and used similar jobs attributes to predict runtimes. Compared with the existing method, experimental results show that the proposed prediction method achieves a similar underestimate rate on the premise of using fewer parameters, and gets a lower mean absolute error. Moreover, on the HPC2N04 and HPC2N05 datasets, the mean absolute errors reduce 43% and 77% respectively. This paper studied the effect of using online prediction to replace user estimation on job scheduling, analyzed the results and pointed out the future improvement directions.

Foundation Support

国家重点研发计划资助项目(2016YFB0201504)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0624
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Algorithm Research & Explore
Pages: 763-767
Serial Number: 1001-3695(2020)03-027-0763-05

Publish History

[2020-03-05] Printed Article

Cite This Article

许伦凡, 熊敏, 肖永浩. 基于调度历史数据在线预测作业执行时间 [J]. 计算机应用研究, 2020, 37 (3): 763-767. (Xu Lunfan, Xiong Min, Xiao Yonghao. On-line prediction of application runtime using schedule historical data [J]. Application Research of Computers, 2020, 37 (3): 763-767. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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