Impacto do uso de contêineres em um serviço de nuvem HTC
Abstract
Container-based virtualization has been gaining significant popularity in recent years by offering isolated virtual environments, with an efficient allocation of computing resources, to applications running on shared systems. This study aims to verify if the improved performance gains are always possible by comparing the use of containers and virtual machines for the execution of a widely used biodiversity application in the context of a cloud service. In particular, the scalability of these virtual environments to support High Throughput Computing is analysed.
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Docker (2016). Docker engine user guide. https://docs.docker.com/engine/userguide/. Acessado em: 01/07/2016.
Felter, W., Ferreira, A., Rajamony, R., and Rubio, J. (2015). An updated performance comparison of virtual machines and linux containers. In IEEE International Sympo- sium on Performance Analysis of Systems and Software (ISPASS), pages 171–172.
Geller, G. N. and Melton, F. (2008). Looking forward: Applying an ecological model web to assess impacts of climate change. Biodiversity, 9(3-4):79–83.
Intel (2016). Intel Virtualization Technology (Intel VT). http://www.intel.com.br/content/www/br/pt/virtualization/virtualization-technology/intel-virtualization-technology.html. Acessado em: 10/08/2016.
KVM (2016). Kernel virtual machine. http://www.linux-kvm.org/page/Main_Page. Acessado em: 10/08/2016.
Muhammad, H. (2016). htop - an interactive process viewer for unix. http://hisham.hm/htop/. Acessado em: 01/07/2016.
OpenMPI (2016). OpenMPI: Open source high performance computing. https://www.open-mpi.org/. Acessado em: 01/07/2016.
Pearce, M., Zeadally, S., and Hunt, R. (2013). Virtualization: Issues, security threats, and solutions. ACM Comput. Surv., 45(2):1–39.
Phillips, S. J., Dudík, M., and Schapire, R. E. (2004). A maximum entropy approach In Proc. of the 21st International Conference on to species distribution modeling. Machine Learning, pages 83–90.
Soltesz, S., Pötzl, H., Fiuczynski, M. E., Bavier, A., and Peterson, L. (2007). Container- based operating system virtualization: A scalable, high-performance alternative to hy- pervisors. In Proc. of the 2nd ACM SIGOPS/EuroSys European Conference on Com- puter Systems 2007, pages 275–287.
Stockwell, D. (1999). The garp modelling system: problems and solutions to automated spatial prediction. International Journal of Geographical Information Science, 13(2):143–158.
Su, Y., Liao, X., Jin, H., and Bell, T. (2010). Data hiding in virtual machine disk images. In IEEE International Conference on Computer and Information Technology (CIT), pages 2278–2283.
VmWare (2016). vsphere e vsphere with operations management. http://www.vmware.com/br/products/vsphere.html. Acessado em: 10/08/2016.
Xavier, M. G., Neves, M. V., and Rose, C. A. F. D. (2014). A performance comparison of container-based virtualization systems for MapReduce clusters. In 2014 22nd Euromi- cro International Conference on Parallel, Distributed, and Network-Based Processing, pages 299–306.
Xavier, M. G., Neves, M. V., Rossi, F. D., Ferreto, T. C., Lange, T., and Rose, C. A. F. D. (2013). Performance evaluation of container-based virtualization for high performance In 21st Euromicro International Conference on Parallel, computing environments. Distributed, and Network-Based Processing, pages 233–240.
Xen (2016). Xen server. http://xenserver.org/. Acessado em: 10/08/2016.
Zarco-González, M. M., Monroy-Vilchis, O., and Alaníz, J. (2013). Spatial model of livestock predation by jaguar and puma in Mexico: Conservation planning. Biological Conservation, 159:80 – 87.
Published
2016-10-05
How to Cite
NICODEMUS, Carlos; BOERES, Cristina; REBELLO, Vinod.
Impacto do uso de contêineres em um serviço de nuvem HTC. In: SYMPOSIUM ON HIGH PERFORMANCE COMPUTING SYSTEMS (SSCAD), 17. , 2016, Aracajú.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 191-202.
DOI: https://doi.org/10.5753/wscad.2016.14259.
