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GCSS: a global collaborative scheduling strategy for wide-area high-performance computing

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Abstract

Wide-area high-performance computing is widely used for large-scale parallel computing applications owing to its high computing and storage resources. However, the geographical distribution of computing and storage resources makes efficient task distribution and data placement more challenging. To achieve a higher system performance, this study proposes a two-level global collaborative scheduling strategy for wide-area high-performance computing environments. The collaborative scheduling strategy integrates lightweight solution selection, redundant data placement and task stealing mechanisms, optimizing task distribution and data placement to achieve efficient computing in wide-area environments. The experimental results indicate that compared with the state-of-the-art collaborative scheduling algorithm HPS+, the proposed scheduling strategy reduces the makespan by 23.24%, improves computing and storage resource utilization by 8.28% and 21.73% respectively, and achieves similar global data migration costs.

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Acknowledgements

This work was supported by the National key R&D Program of China (2018YFB0203901), the National Natural Science Foundation of China under (Grant No. 61772053), and the fund of the State Key Laboratory of Software Development Environment (SKLSDE-2020ZX-15).

Author information

Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, 100191, China

    Yao Song, Limin Xiao, Bing Wei, Baicheng Yan & Chenhao Zhang

  2. School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Yao Song, Limin Xiao, Liang Wang, Bing Wei, Baicheng Yan & Chenhao Zhang

  3. Smart City College, Beijing Union University, Beijing, 100101, China

    Guangjun Qin

Authors
  1. Yao Song
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  2. Limin Xiao
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  4. Guangjun Qin
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  5. Bing Wei
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  7. Chenhao Zhang
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Corresponding authors

Correspondence to Limin Xiao or Guangjun Qin.

Additional information

Yao Song received his BS degree in spacecraft design and engineering from Beihang University, China in 2016. He is currently pursuing his PhD degree in cyberspace security at Beihang University. His main research interests include cyberspace security, parallel and distributed file systems, high performance computing, and scheduling system.

Limin Xiao received his BS degree in computer science from Tsinghua University, China in 1993, his MS and PhD degrees in computer science from Institute of computing, Chinese Academy of Sciences, China in 1996 and 1998, respectively. He is a professor of the School of Computer Science and Engineering, Beihang University, China. He is a senior membership of China Computer Federation. His main research areas are computer architecture, computer system software, high performance computing, virtualization and cloud computing.

Liang Wang received his BS and MS degrees in electronics engineering from Harbin Institute of Technology, China in 2011 and 2013 respectively, and his PhD degree in computer science and engineering from University of Hong Kong, China in 2017. He is currently an assistant professor with the School of Computer Science and Engineering, Beihang University, China. He was a postdoctoral research fellow in Institute of Microelectronics, Tsinghua University, China during 2017 and 2020. His research interests include power-efficient and reliability-aware design for network-on-chip and many-core system.

Guangjun Qin received his MS degree in computer application technology in Zhengzhou University, China in 2006 and his PhD degree in computer architecture from Beihang University, China in 2015. From 2015 to 2017, he was a postdoctoral fellow at Beihang University, China. Since 2017, he has been a lecturer of Smart City College, Beijing Union University, China. He is the author of one book, more than 20 articles, and a member of China Computer Federation. His main research areas are computer architecture, information security and big data analysis.

Bing Wei received his BS degree in electrical engineering and MS degree in computer science from Capital Normal University, China in 2012 and 2015, respectively, He is currently pursuing his PhD degree in computer science at Beihang University, China. His main research interests include file systems, high performance computing, software engineering and clusters.

Baicheng Yan received his BS degree in computer science and technology from Harbin Engineering University, China in 2016. He is currently pursuing his PhD degree in computer science at Beihang University, China. His research interests include high performance computing, parallel and distributed computing.

Chenhao Zhang received his BS degree in Internet of Things engineering from China University of Petroleum (East China), China in 2019. He is currently pursuing his PhD degree in computer science at Beihang University, China. His main research interests include distributed file systems, storage system, high performance computing, bigdata analysis and computer system software.

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Song, Y., Xiao, L., Wang, L. et al. GCSS: a global collaborative scheduling strategy for wide-area high-performance computing. Front. Comput. Sci. 16, 165105 (2022). https://doi.org/10.1007/s11704-021-0353-5

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