Análise de Desempenho de um Simulador de Reservatórios de Petróleo em um Ambiente de Computação em Nuvem
Abstract
Cloud Computing is a distributed computing paradigm which customers access computing resources from the Internet. Recent researches investigate the use of clouds to perform scientific computing that requires a lot of computing power. In this paper we present a performance analysis of a real petroleum reservoir simulator in a cloud environment provided by both Amazon EC2 and Microsoft Azure platforms. This performance analysis takes into account metrics related to operational system and the results of some specific benchmarks. The results show that virtualization overhead and resource sharing can drastically decrease performance of such applications.References
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Ramakrishnan, L., Zbiegel, P. T., Campbell, S., Bradshaw, R., Canon, R. S., Coghlan, S., Sakrejda, I., Desai, N., Declerck, T., and Liu, A. (2011). Magellan: experiences from a science cloud. In Proceedings of the 2nd international workshop on Scientic cloud computing, pages 49–58. ACM.
Subramanian, V., Ma, H., Wang, L., Lee, E.-J., and Chen, P. (2011). Rapid 3d seismic source inversion using windows azure and amazon ec2. In Services (SERVICES), 2011 IEEE World Congress on, pages 602–606. IEEE.
Vecchiola, C., Pandey, S., and Buyya, R. (2009). High-performance cloud computing: In Pervasive Systems, Algorithms, and Networks A view of scientic applications. (ISPAN), 2009 10th International Symposium on, pages 4–16. IEEE.
Vöckler, J.-S., Juve, G., Deelman, E., Rynge, M., and Berriman, B. (2011). Experiences using cloud computing for a scientic workow application. In Proceedings of the 2nd international workshop on Scientic cloud computing, pages 15–24. ACM.
Deshane, T., Shepherd, Z., Matthews, J., Ben-Yehuda, M., Shah, A., and Rao, B. (2008). Quantitative comparison of xen and kvm. Xen Summit, Boston, MA, USA, pages 1–2.
He, Q., Zhou, S., Kobler, B., Duffy, D., and McGlynn, T. (2010). Case study for running hpc applications in public clouds. In Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, pages 395–401. ACM.
Heilmann, Z., Deidda, G., Satta, G., and Bonomi, E. (2013). Real-time imaging and data analysis for shallow seismic data using a cloud-computing portal. Near Surface Geophysics, 11(4):407–421.
Hennessy, J. L. and Patterson, D. A. (2012). Computer architecture: a quantitative ap proach. Elsevier.
Hoffa, C., Mehta, G., Freeman, T., Deelman, E., Keahey, K., Berriman, B., and Good, J. (2008). On the use of cloud computing for scientic workows. In eScience, 2008. eScience’08. IEEE Fourth International Conference on, pages 640–645. IEEE.
Jackson, K. R., Ramakrishnan, L., Muriki, K., Canon, S., Cholia, S., Shalf, J., Wasserman, H. J., and Wright, N. J. (2010). Performance analysis of high performance computing applications on the amazon web services cloud. In Cloud Computing Technology and Science (CloudCom), 2010 IEEE Second International Conference on, pages 159–168. IEEE.
Knight, D., Shams, K., Chang, G., and Soderstrom, T. (2012). Evaluating the efcacy of the cloud for cluster computation. In Aerospace Conference, 2012 IEEE, pages 1–10. IEEE.
Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., and Epema, D. (2010). A performance analysis of ec2 cloud computing services for scientic computing. In Cloud Computing, pages 115–131. Springer.
Peaceman, D. W. (2000). Fundamentals of numerical reservoir simulation. Elsevier.
Popiolek, P. F. and Mendizabal, O. M. (2013). Monitoring and analysis of performance impact in virtualized environments. Journal of Applied Computing Research, 2(2):75– 82.
Ramakrishnan, L., Zbiegel, P. T., Campbell, S., Bradshaw, R., Canon, R. S., Coghlan, S., Sakrejda, I., Desai, N., Declerck, T., and Liu, A. (2011). Magellan: experiences from a science cloud. In Proceedings of the 2nd international workshop on Scientic cloud computing, pages 49–58. ACM.
Subramanian, V., Ma, H., Wang, L., Lee, E.-J., and Chen, P. (2011). Rapid 3d seismic source inversion using windows azure and amazon ec2. In Services (SERVICES), 2011 IEEE World Congress on, pages 602–606. IEEE.
Vecchiola, C., Pandey, S., and Buyya, R. (2009). High-performance cloud computing: In Pervasive Systems, Algorithms, and Networks A view of scientic applications. (ISPAN), 2009 10th International Symposium on, pages 4–16. IEEE.
Vöckler, J.-S., Juve, G., Deelman, E., Rynge, M., and Berriman, B. (2011). Experiences using cloud computing for a scientic workow application. In Proceedings of the 2nd international workshop on Scientic cloud computing, pages 15–24. ACM.
Published
2014-10-08
How to Cite
ALVES, Maicon; DRUMMOND, Lúcia Maria.
Análise de Desempenho de um Simulador de Reservatórios de Petróleo em um Ambiente de Computação em Nuvem. In: SYMPOSIUM ON HIGH PERFORMANCE COMPUTING SYSTEMS (SSCAD), 15. , 2014, São José dos Campos.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2014
.
p. 51-62.
DOI: https://doi.org/10.5753/wscad.2014.14999.
