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IFIP International Conference on Network and Parallel Computing

NPC 2012: Network and Parallel Computing pp 22–32Cite as

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Knowledge-Based Adaptive Self-Scheduling

Knowledge-Based Adaptive Self-Scheduling

  • Yizhuo Wang20,
  • Weixing Ji20,
  • Feng Shi20,
  • Qi Zuo20 &
  • …
  • Ning Deng20 
  • Conference paper
  • 2281 Accesses

  • 6 Citations

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7513)

Abstract

Loop scheduling scheme plays a critical role in the efficient execution of programs, especially loop dominated applications. This paper presents KASS, a knowledge-based adaptive loop scheduling scheme. KASS consists of two phases: static partitioning and dynamic scheduling. To balance the workload, the knowledge of loop features and the capabilities of processors are both taken into account using a heuristic approach in static partitioning phase. In dynamic scheduling phase, an adaptive self-scheduling algorithm is applied, in which two tuning parameters are set to control chunk sizes, aiming at load balancing and minimizing synchronization overhead. In addition, we extend KASS to apply on loop nests and adjust the chunk sizes at runtime. The experimental results show that KASS performs 4.8% to 16.9% better than the existing self- scheduling schemes, and up to 21% better than the affinity scheduling scheme.

Keywords

  • loop scheduling
  • self-scheduling
  • multiprocessor system

This work was supported by the National Natural Science Foundation of China (60973010).

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Beijing Institute of Technology, China

    Yizhuo Wang, Weixing Ji, Feng Shi, Qi Zuo & Ning Deng

Authors
  1. Yizhuo Wang
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  2. Weixing Ji
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  3. Feng Shi
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  4. Qi Zuo
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  5. Ning Deng
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, SeoulTech, 172 Gongreung 2-dong, Nowon-gu, 139-743, Seoul, Korea

    James J. Park

  2. School of Information Technologies, The University of Sydney, Building J12, 2006, Sydney, NSW, Australia

    Albert Zomaya

  3. Division of Computer Engineering, Mokwon University, 88 Do-An-Buk-Ro, Seo-gu, 302-729, Daejeon, Korea

    Sang-Soo Yeo

  4. Department of Computer and Information Science and Engineering, University of Florida, CSE 301, 32611, Gainesville, FL, USA

    Sartaj Sahni

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© 2012 IFIP International Federation for Information Processing

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Cite this paper

Wang, Y., Ji, W., Shi, F., Zuo, Q., Deng, N. (2012). Knowledge-Based Adaptive Self-Scheduling. In: Park, J.J., Zomaya, A., Yeo, SS., Sahni, S. (eds) Network and Parallel Computing. NPC 2012. Lecture Notes in Computer Science, vol 7513. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35606-3_3

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  • DOI: https://doi.org/10.1007/978-3-642-35606-3_3

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  • Print ISBN: 978-3-642-35605-6

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