Avaliação da Escalabilidade de Aplicações de Alto Desempenho em Nuvem Pública e Privada
Abstract
The high performance computing application analysis (HPC), has recently been facilitated by the use of cloud platforms. However, the performance of HPC applications relies heavily on the support I/O platform, mainly the communication network between the VMs 1. In this study, the application performance of the NPB-NAS Parallel Benchmark suite and DGEO suite, which uses processing spatial queries was compared in a physical cluster, a private cloud, XenServer, a public cloud, Microsoft Azure. The tests demonstrate one speed up to 3.0 times lower in the public cloud for limited by CPU applications, and a runtime up to 3 times greater than the physical cluster. The speed-up between cloud platforms tested here was analyzed that it is not only affected by the extra layer of virtualization, but also by other factors platform cloud as VMs neighbors.
References
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AMD. AMD I/O Virtualization Technology (IOMMU) Specication. White Paper, AMD: http://developer.amd.com/wordpress/media/2012/10/488821.pdf, v. 2.00, 2011.
BAILEY, D. H. et al. The nas parallel benchmarks. International Journal of High Performance Computing Applications, SAGE Publications, v. 5, n. 3, p. 63–73, 1991.
BAKHSHAYESHI, R.; AKBARI, M. K.; JAVAN, M. S. Performance Analysis of Virtualized Environments Using HPC Challenge Benchmark Suite and Analytic Hierarchy Process. In: Intelligent Systems (ICIS), 2014 Iranian Conference on. Higher Education Complex of Bam, Highway Persian Gulf, Bam, Iran: [s.n.], 2014. p. 1–6.
BARKER, S. K.; SHENOY, P. Empirical Evaluation of Latency-sensitive Application Performance in the Cloud. In: Proceedings of the First Annual ACM SIGMM Conference on Multimedia Systems. New York, NY, USA: ACM, 2010. p. 35–46.
EXPíOSITO, R. R. et al. Performance analysis of hpc applications in the cloud. Future Generation Computer Systems, Elsevier, v. 29, n. 1, p. 218–229, 2013.
FERREIRA, C. H. et al. Identicação de Gargalos de Desempenho em Ambientes Virtuais para uso em Computação em Nuvem. XIII Workshop em Desempenho de Sistemas Computacionais e de Comunicação, Braília DF, Brasil, p. 1 – 14, 2014.
HILL, Z. et al. Early Observations on the Performance of Windows Azure. In: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing. New York, NY, USA: ACM, 2010. (HPDC '10), p. 367–376.
HUBER, N. et al. Evaluating and modeling virtualization performance overhead for cloud environments. In: CLOSER. [S.l.: s.n.], 2011. p. 563–573.
MEI, Y. et al. Performance Analysis of Network I/O Workloads in Virtualized Data Centers. Services Computing, IEEE Transactions on, IEEE Transactions on Services Computing, p. 48–63, 2013.
OLIVEIRA, T. B. de; COSTA, F. M.; RODRIGUES, V. J. S. Denição de Planos de Execução Distribuídos para Consultas de Junção Espacial usando Histogramas Multidimensionais. In: Proc. of XXX SBBD. Petrópolis: [s.n.], 2015. p. 89–100.
OLIVEIRA, T. B. de et al. Avaliação Comparativa de Escalabilidade de Aplicações de Alto Desempenho em Cluster Físico e na Nuvem. In: Anais do WPerformance CSBC 2015. Recife: [s.n.], 2015. p. 1–12.
SIVATHANU, S.; DONG, X. Performance analysis of network i/o workloads in virtualized data centers. IEEE Transactions on Services Computing, p. 48–63, 2013.
TUDORAN, R. et al. A Performance Evaluation of Azure and Nimbus Clouds for Scientic Applications. In: Proceedings of the 2Nd International Workshop on Cloud Computing Platforms. New York, NY, USA: ACM, 2012. p. 4:1–4:6.
WALTERS, J. P. et al. A comparison of virtualization technologies for hpc. In: IEEE. 22nd International Conference on Advanced Information Networking and Applications (aina 2008). [S.l.], 2008. p. 861–868.
YOUNGE, A. J. et al. Analysis of virtualization technologies for high performance computing environments. In: IEEE. Cloud Computing (CLOUD), 2011 IEEE International Conference on. [S.l.], 2011. p. 9–16.
Published
2016-10-05
How to Cite
SILVA, Ariel; DE OLIVEIRA, Thiago.
Avaliação da Escalabilidade de Aplicações de Alto Desempenho em Nuvem Pública e Privada. In: SYMPOSIUM ON HIGH PERFORMANCE COMPUTING SYSTEMS (SSCAD), 17. , 2016, Aracajú.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 215-226.
DOI: https://doi.org/10.5753/wscad.2016.14261.
