Abstract
This article presents an empirical evaluation of power consumption of synthetic benchmarks in multicore computing systems. The study aims at providing an insight of the main power consumption characteristics of different applications when executing over current high performance computing servers. Three types of applications are studied executing individually and simultaneously on the same server. Intel and AMD architectures are studied in an experimental setting for evaluating the overall power consumption of each application. The main results indicate the power consumption behavior has a strong dependency with the type of application. An additional performance analysis shows that the best load of the server regarding energy efficiency depends on the type of the applications, with efficiency decreasing in heavily loaded situations. These results allow characterizing applications according to power consumption, efficiency, and resource sharing, and provide useful information for resource management and scheduling policies.
Keywords
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 subscriptionsReferences
Anghel, A., Vasilescu, L., Mariani, G., Jongerius, R., Dittmann, G.: An instrumentation approach for hardware-agnostic software characterization. Int. J. Parallel Prog. 44(5), 924–948 (2016)
Brandolese, C., Corbetta, S., Fornaciari, W.: Software energy estimation based on statistical characterization of intermediate compilation code. In: International Symposium on Low Power Electronics and Design, pp. 333–338 (2011)
Buyya, R., Vecchiola, C., Selvi, S.: Mastering Cloud Computing: Foundations and Applications Programming. Morgan Kaufmann, San Francisco (2013)
Dayarathna, M., Wen, Y., Fan, R.: Data center energy consumption modeling: a survey. IEEE Commun. Surv. Tutorials 18(1), 732–794 (2016)
Du Bois, K., Schaeps, T., Polfliet, S., Ryckbosch, F., Eeckhout, L.: Sweep: evaluating computer system energy efficiency using synthetic workloads. In: 6th International Conference on High Performance and Embedded Architectures and Compilers, pp. 159–166 (2011)
Feng, X., Ge, R., Cameron, K.: Power and energy profiling of scientific applications on distributed systems. In: 19th IEEE International Parallel and Distributed Processing Symposium, pp. 34–44 (2005)
Iturriaga, S., García, S., Nesmachnow, S.: An empirical study of the robustness of energy-aware schedulers for high performance computing systems under uncertainty. In: Hernández, G., Barrios Hernández, C.J., Díaz, G., García Garino, C., Nesmachnow, S., Pérez-Acle, T., Storti, M., Vázquez, M. (eds.) CARLA 2014. CCIS, vol. 485, pp. 143–157. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45483-1_11
Kopytov, A.: Sysbench repository https://github.com/akopytov/sysbench. Accessed 1 May 2017
Kurowski, K., Oleksiak, A., Piątek, W., Piontek, T., Przybyszewski, A., Węglarz, J.: Dcworms-a tool for simulation of energy efficiency in distributed computing infrastructures. Simul. Model. Pract. Theory 39, 135–151 (2013)
Langer, A., Totoni, E., Palekar, U.S., Kalé, L.V.: Energy-efficient computing for HPC workloads on heterogeneous manycore chips. In: Proceedings of the Sixth International Workshop on Programming Models and Applications for Multicores and Manycores, pp. 11–19 (2015)
Nesmachnow, S.: Computación científica de alto desempeño en la Facultad de Ingeniería. Universidad de la República. Revista de la Asociación de Ingenieros del Uruguay, 61(1), pp. 12–15 (2010). Text in Spanish
Nesmachnow, S., Dorronsoro, B., Pecero, J., Bouvry, P.: Energy-aware scheduling on multicore heterogeneous grid computing systems. J. Grid Comput. 11(4), 653–680 (2013)
Nesmachnow, S., Perfumo, C., Goiri, I.: Holistic multiobjective planning of datacenters powered by renewable energy. Cluster Comput. 18(4), 1379–1397 (2015)
Srikantaiah, S., Kansal, A., Zhao, F.: Energy aware consolidation for cloud computing. In: Conference on Power Aware Computing and Systems, vol. 10, pp. 1–5 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Muraña, J., Nesmachnow, S., Iturriaga, S., Tchernykh, A. (2018). Power Consumption Characterization of Synthetic Benchmarks in Multicores. In: Mocskos, E., Nesmachnow, S. (eds) High Performance Computing. CARLA 2017. Communications in Computer and Information Science, vol 796. Springer, Cham. https://doi.org/10.1007/978-3-319-73353-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-73353-1_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73352-4
Online ISBN: 978-3-319-73353-1
eBook Packages: Computer ScienceComputer Science (R0)