MA Yan, GONG Bin, GUO Zhihong, et al., “Energy-Aware Scheduling of Parallel Application in Hybrid Computing System,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 688-694, 2014,
Citation: MA Yan, GONG Bin, GUO Zhihong, et al., “Energy-Aware Scheduling of Parallel Application in Hybrid Computing System,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 688-694, 2014,

Energy-Aware Scheduling of Parallel Application in Hybrid Computing System

  • Received Date: 2014-01-01
  • Rev Recd Date: 2014-02-01
  • Publish Date: 2014-10-05
  • Energy management is emerging as an important issue for High performance computing (HPC) owning to high operational cost and low reliability. Compared with low-power architectural approach, energy-aware scheduling based on Dynamic voltage scaling (DVS) and Dynamic power management (DPM) is regarded as a promising way since it is practical and low-cost. At present, most studies focus on pure DVS or non-DVS environment, while most high performance computing systems are hybrid non-DVS/DVS platforms. We propose an energy-aware scheduling algorithm for parallel application to consider both DVS and non-DVS characteristics of hybrid system. We present the rule of task assignment, make analysis on DVS and DPM technique and give their mathematical formulation, which maintains makespan optimization and energy conservation. The clustering and merging algorithm, and priority computation method consider the situation of resource constraints. The extensive simulations demonstrate that the proposed algorithm has stronger ability of energy saving and time optimization than Heterogeneous earliest finish time (HEFT), Energy-efficient task duplication scheduling (EETDS) and Heterogeneous energy-aware duplication scheduling (HEADUS) algorithm no matter for synthetic workload or realistic workload.
  • loading
  • K.H. Kim, R. Buyya and J. Kim, Power aware scheduling of bag-of-tasks applications with deadline constraints on DVS-enabled clusters, Proc. 7th Cluster Computing and the Grid (CCGRID), Rio de Janeiro, Brazil, pp.541-548, 2007.
    Z. Zong, Energy-Efficient Resource Management for High-Performance Computing Platforms, Ph.D. thesis, Auburn University, USA, 2008.
    J. Han, Q. Li and A. Essa, Dynamic power-aware scheduling algorithms for real-time task sets in parallel and distributed computing environments, Chinese Journal of Electronics, Vol.15, No.1, pp.41-46, 2006.
    M. Sharifi, S. Shahrivari and H. Salimi, Pasta: A power-aware solution to scheduling of precedence-constrained tasks on heterogeneous computing resources, Computing, Vol.95, No.1, pp.67-88, 2013.
    H. Al-Daoud, I. Al-Azzoni and D.G. Down, Power-aware linear programming based scheduling for heterogeneous computer clusters, Future Generation Computer Systems, Vol.28, No.5, pp.745-754, 2012.
    Y. Ma, B. Gong, R. Sugihara and R. Gupta, Energy-efficient deadline scheduling for heterogeneous systems, J. Parallel Distrib. Comput., Vol.72, No.12, pp.1725-1740, 2012.
    C.Y. Yang, J.J. Chen, T.W. Kuo and L. Thiele, Energy reduction techniques for systems with non-dvs components, Proc. IEEE Conference on Emerging Technologies and Factory Automation (ETFA), Mallorca, Spain, pp.1-8, 2009.
    L. Niu, Rate-monotonic scheduling for reducing system-wide energy consumption for hard real-time systems, Proc. Conference on Computer Design, Amsterdam, The Netherlands, pp.159-165, 2010.
    C.-M. Hung, J.-J. Chen and T.-W. Kuo, Energy-efficient real-time task scheduling for a dvs system with a non-dvs processing element, Proc. 27th IEEE Conference on Real-time Systems (RTSS), Rio de Janeiro, Brazil, pp.293-300, 2006.
    Y. Ma, B. Gong and L. Zou, Energy-efficient scheduling algorithm of task dependent graph on DVS-unable cluster system, Proc. 10th Conference on Grid Computing (GRID), Banff, Alberta, Canada, pp.217-224, 2009.
    P.D. Langen and B. juurlink, Leakage-aware multiprocessor scheduling for low power, Proc. 20th IEEE International Parallel and Distributed Processing Symp (IPDPS), Rhodes Island, Greece, pp.1-8, 2006.
    J. Liou and M. A. Palis, An efficient task clustering heuristic for scheduling DAGs on multiprocessors, Workshop on Resource Management, Symposium on Parallel and Distributed Processing, pp.152-156, Citeseer, 1996.
    H. Topcuoglu, Min-You Wu and S. Hariri, Performance-effective and low-complexity task scheduling for heterogeneous computing, IEEE Trans. Parallel Dist. Systems, Vol.13, No.3, pp.260-274, 2002.
  • 加载中


    通讯作者: 陈斌,
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (478) PDF downloads(902) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint