Simulation-Based Performance Evaluation of an Energy-Aware Heuristic for the Scheduling of HPC Applications in Large-Scale Distributed Systems

ABSTRACT

As the distributed resources required for the processing of High Performance Computing (HPC) applications are becoming larger in scale and computational capacity, their energy consumption has become a major concern. Therefore, there is a growing focus from both the academia and the industry on the minimization of the carbon footprint of the computational resources, especially through the efficient scheduling of the workload. In this paper, a technique is proposed for the energy-aware scheduling of bag-of-tasks applications with time constraints in a large-scale heterogeneous distributed system. Its performance is evaluated by simulation and compared with a baseline algorithm. The simulation results show that the proposed heuristic not only reduces the energy consumption of the system, but also improves its performance.

References

1. Specpower\_ssj2008. https://www.spec.org/power_ssj2008/results/power_ssj2008.html. Last update: 21 Dec. 2016.
2. A. Beloglazov, J. Abawajy, and R. Buyya. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 28(5):755--768, May 2012.
3. A. Beloglazov and R. Buyya. Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers. In Proceedings of the 8th International Workshop on Middleware for Grids, Clouds and e-Science (MGC'10), pages 4:1--4:6, Nov. 2010.
4. G. C. Buttazzo. Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications. Springer, 3rd edition, 2011.
5. R. N. Calheiros and R. Buyya. Energy-efficient scheduling of urgent bag-of-tasks applications in clouds through dvfs. In Proceedings of the 6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom'14), pages 342--349, Dec. 2014.
6. R. F. Freund, M. Gherrity, S. Ambrosius, M. Campbell, M. Halderman, D. Hensgen, E. Keith, T. Kidd, M. Kussow, J. D. Lima, F. Mirabile, L. Moore, B. Rust, and H. J. Siegel. Scheduling resources in multi-user, heterogeneous, computing environments with smartnet. In Proceedings of the 7th Heterogeneous Computing Workshop (HCW'98), pages 184--199, Mar. 1998.
7. O. H. Ibarra and C. E. Kim. Heuristic algorithms for scheduling independent tasks on nonidentical processors. Journal of the ACM, 24(2):280--289, Apr. 1977.
8. H. D. Karatza. Performance of gang scheduling strategies in a parallel system. Simulation Modelling Practice and Theory, 17(2):430--441, Feb. 2009.
9. K. H. Kim, R. Buyya, and J. Kim. Power aware scheduling of bag-of-tasks applications with deadline constraints on dvs-enabled clusters. In Proceedings of the 7th IEEE International Symposium on Cluster Computing and the Grid (CCGrid'07), pages 541--548, May 2007.
10. Y. Li, Y. Liu, and D. Qian. A heuristic energy-aware scheduling algorithm for heterogeneous clusters. In Proceedings of the 15th International Conference on Parallel and Distributed Systems (ICPADS'09), pages 407--413, Dec. 2009.
11. C. L. Liu and J. W. Layland. Scheduling algorithms for multiprogramming in a hard real-time environment. Journal of the ACM, 20(1):46--61, Jan. 1973.
12. S. Nesmachnow, B. Dorronsoro, J. E. Pecero, and P. Bouvry. Energy-aware scheduling on multicore heterogeneous grid computing systems. Journal of Grid Computing, 11(4):653--680, Dec. 2013.
13. N. Quang-Hung, P. D. Nien, N. H. Nam, N. Huynh Tuong, and N. Thoai. A genetic algorithm for power-aware virtual machine allocation in private cloud. In Proceedings of the 2013 Information and Communication Technology - EurAsia Conference (ICT-EurAsia'13), pages 25--29, Mar. 2013.
14. H. Senger, E. R. Hruschka, F. A. B. Silva, L. M. Sato, C. P. Bianchini, and B. F. Jerosch. Exploiting idle cycles to execute data mining applications on clusters of pcs. Journal of Systems and Software, 80(5):778--790, May 2007.
15. F. A. B. Silva and H. Senger. Scalability limits of bag-of-tasks applications running on hierarchical platforms. Journal of Parallel and Distributed Computing, 71(6):788--801, June 2011.
16. G. L. Stavrinides, F. R. Duro, H. D. Karatza, J. G. Blas, and J. Carretero. Different aspects of workflow scheduling in large-scale distributed systems. Simulation Modelling Practice and Theory, 70:120--134, Jan. 2017.
17. G. L. Stavrinides and H. D. Karatza. The impact of input error on the scheduling of task graphs with imprecise computations in heterogeneous distributed real-time systems. In Proceedings of the 18th International Conference on Analytical and Stochastic Modelling Techniques and Applications (ASMTA'11), pages 273--287, June 2011.
18. G. L. Stavrinides and H. D. Karatza. Scheduling real-time dags in heterogeneous clusters by combining imprecise computations and bin packing techniques for the exploitation of schedule holes. Future Generation Computer Systems, 28(7):977--988, July 2012.
19. G. L. Stavrinides and H. D. Karatza. A cost-effective and qos-aware approach to scheduling real-time workflow applications in paas and saas clouds. In Proceedings of the 3rd International Conference on Future Internet of Things and Cloud (FiCloud'15), pages 231--239, Aug. 2015.
20. G. L. Stavrinides and H. D. Karatza. Scheduling real-time parallel applications in saas clouds in the presence of transient software failures. In Proceedings of the 2016 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS'16), pages 1--8, July 2016.
21. E. K. Tabak, B. B. Cambazoglu, and C. Aykanat. Improving the performance of independent task assignment heuristics minmin, maxmin and sufferage. IEEE Transactions on Parallel and Distributed Systems, 25(5):1244--1256, May 2014.
22. H. K. Tang, P. Ramanathan, and K. Morrow. Inserting placeholder slack to improve run-time scheduling of non-preemptible real-time tasks in heterogeneous systems. In Proceedings of the 27th International Conference on VLSI Design and 13th International Conference on Embedded Systems 2014, pages 168--173, Jan. 2014.
23. G. Terzopoulos and H. D. Karatza. Power-aware bag-of-tasks scheduling on heterogeneous platforms. Cluster Computing, 19(2):615--631, June 2016.
24. G. L. Valentini, W. Lassonde, S. U. Khan, N. Min-Allah, S. A. Madani, J. Li, L. Zhang, L. Wang, N. Ghani, J. Kolodziej, H. Li, A. Y. Zomaya, C. Z. Xu, P. Balaji, A. Vishnu, F. Pinel, J. E. Pecero, D. Kliazovich, and P. Bouvry. An overview of energy efficiency techniques in cluster computing systems. Cluster Computing, 16(1):3--15, Mar. 2013.
25. C. Weng and X. Lu. Heuristic scheduling for bag-of-tasks applications in combination with qos in the computational grid. Future Generation Computer Systems, 21(2):271--280, Feb. 2005.
26. X. Zhu, X. Qin, and M. Qiu. Qos-aware fault-tolerant scheduling for real-time tasks on heterogeneous clusters. IEEE Transactions on Computers, 60(6):800--812, June 2011.

Index Terms

• Computer systems organization

  • Architectures

    • Distributed architectures

  • Real-time systems

• Computing methodologies

  • Modeling and simulation

• Hardware

  • Power and energy

• Software and its engineering

  • Software organization and properties

    • Contextual software domains

      • Operating systems

        • Process management

          • Scheduling