Abstract
This article presents an empirical evaluation of energy-aware schedulers under uncertainties in both the execution time of tasks and the energy consumption of the computing infrastructure. We address an important problem with direct application in current clusters and distributed computing systems, by analyzing how the list scheduling techniques proposed in a previous work behave when considering errors in the execution time estimation of tasks and realistic deviations in the power consumption. The experimental evaluation is performed over realistic workloads and scenarios, and validated by in-situ measurements using a power distribution unit. Results demonstrate that errors in real-world scenarios have a significant impact on the accuracy of the scheduling algorithms. Different online and offline scheduling approaches were evaluated, and online approach showed improvements of up to 32% in computing performance and up to 18% in energy consumption over the offline approach using the same scheduling algorithm.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Ahmad, I., Ranka, S.: Handbook of Energy-Aware and Green Computing. Chapman & Hall/CRC (2012)
Ali, S., Maciejewski, A., Siegel, H., Kim, J.: Measuring the robustness of a resource allocation. IEEE Trans. Parallel Distrib. Syst. 51(7), 630–641 (2004)
Bailey Lee, C., Schwartzman, Y., Hardy, J., Snavely, A.: Are user runtime estimates inherently inaccurate? In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2004. LNCS, vol. 3277, pp. 253–263. Springer, Heidelberg (2005)
Brigham, O.: The Fast Fourier Transform. Prentice-Hall, New Jersey (1974)
Cirne, W., Berman, F.: A comprehensive model of the supercomputer workload. In: International Workshop on Workload Characterization, pp. 140–148 (2001)
Dongarra, J.: The LINPACK benchmark: An explanation. In: Proceedings of the 1st International Conference on Supercomputing, pp. 456–474 (1988)
Dorronsoro, B., Bouvry, P., Cañero, J., Maciejewski, A., Siegel, H.: Multi-objective robust static mapping of independent tasks on grids. In: IEEE Congress on Evolutionary Computation, pp. 3389–3396 (2010)
Feitelson, D.G., Rudolph, L., Schwiegelshohn, U.: Parallel job scheduling a status report. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2004. LNCS, vol. 3277, pp. 1–16. Springer, Heidelberg (2005)
Ghafoor, A., Yang, J.: Distributed heterogeneous supercomputing management system. IEEE Comput. 26(6), 78–86 (1993)
Kafil, M., Ahmad, I.: Optimal task assignment in heterogeneous distributed computing systems. IEEE Concurrency 6(3), 42–51 (1998)
Lee, Y., Zomaya, A.: Minimizing energy consumption for precedence-constrained applications using dynamic voltage scaling. In: Proc. of the 9th International Symposium on Cluster Computing and the Grid, Shanghai, China, pp. 92–99 (2009)
Leung, J., Kelly, L., Anderson, J.H.: Handbook of Scheduling: Algorithms, Models, and Performance Analysis. CRC Press, Inc., Boca Raton (2004)
Mehta, A., Smith, J., Siegel, H., Maciejewski, A., Jayaseelan, A., Ye, B.: Dynamic resource allocation heuristics that manage tradeoff between makespan and robustness. Journal of Supercomputing, Special Issue on Grid Technology 42(1), 33–58 (2007)
Minh, T.N., Wolters, L.: Using historical data to predict application runtimes on backfilling parallel systems. In: 18th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, pp. 246–252 (February 2010)
Mu’alem, A., Feitelson, D.: Utilization, predictability, workloads, and user runtime estimates in scheduling the ibm sp2 with backfilling. IEEE Trans. Parallel Distrib. Syst. 12(6), 529–543 (2001)
Nesmachnow, S., Dorronsoro, B., Pecero, J.E., Bouvry, P.: Energy-aware scheduling on multicore heterogeneous grid computing systems. Journal of Grid Computing 11(4), 653–680 (2013)
Shmueli, E., Feitelson, D.: On simulation and design of parallel-systems schedulers: Are we doing the right thing? IEEE Trans. Parallel Distrib. Syst. 20(7), 983–996 (2009)
Tang, W., Desai, N., Buettner, D., Lan, Z.: Job scheduling with adjusted runtime estimates on production supercomputers. Journal of Parallel and Distributed Computing 73(7), 926–938 (2013)
Tsafrir, D.: Using inaccurate estimates accurately. In: Frachtenberg, E., Schwiegelshohn, U. (eds.) JSSPP 2010. LNCS, vol. 6253, pp. 208–221. Springer, Heidelberg (2010)
Zhu, D., Melhem, R., Childers, B.: Scheduling with dynamic voltage/speed adjustment using slack reclamation in multiprocessor real-time systems. IEEE Trans. Parallel Distrib. Syst. 14, 686–700 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Iturriaga, S., García, S., Nesmachnow, S. (2014). An Empirical Study of the Robustness of Energy-Aware Schedulers for High Performance Computing Systems under Uncertainty. In: Hernández, G., et al. High Performance Computing. CARLA 2014. Communications in Computer and Information Science, vol 485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45483-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-662-45483-1_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45482-4
Online ISBN: 978-3-662-45483-1
eBook Packages: Computer ScienceComputer Science (R0)