Virtualization of heterogeneous HPC-clusters based on OpenStack platform

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The paper addresses to the problem of integration of heterogeneous computing clusters to the united environment based on a virtualization technology. OpenStack software is selected as a platform for managing the virtual environment. The OpenStack platform provides a wide range of components and solutions to a functional interaction with different hypervisors. These include KVM, XEN, ESXi, QEMU and other systems. In addition to the OpenStack platform, we developed a specialized hypervisor shell. It helps to start virtual machines using queues of the traditional resource management systems, such as PBS, SLURM, LSF, or SGE, that are used on clusters of a center of collective usage. The developed model of the resource allocation for virtual machines allowed us to use the knowledge about job requests, resource characteristics and current state of the environment, and the expertise of it administrators. The realized tools provide the capability for the “painless” integration of heterogeneous clusters with the preinstalled local resource managers for creating the virtual cluster with the required configuration. Extensive modeling shows that the hypervisor shell can improve efficiency of integrated environment nodes through reallocating virtual machines to queues of the traditional resource management systems.

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Computer clusters, hpc, virtualization technologies, openstack, simulation modeling

Короткий адрес: https://sciup.org/147160618

IDR: 147160618   |   DOI: 10.14529/cmse170203

Список литературы Virtualization of heterogeneous HPC-clusters based on OpenStack platform

  • Gergel V., Senin A. Metacluster System for Managing the HPC Integrated Environment//Methods and Tools of Parallel Programming Multicomputers. Second Russia-Taiwan Symposium, MTPP 2010 (Vladivostok, Russia, May 16-19 2010). LNCS, Vol. 6083. P. 86-94 DOI: 10.1007/978-3-642-14822-4
  • Mladen A., Eric S., Patrick D. Integration of High-Performance Computing into Cloud Computing Services//Handbook of Cloud Computing. 2010. P. 255-276 DOI: 10.1007/978-1-4419-6524-0_11
  • Бычков И.В., Опарин Г.А., Новопашин А.П., Феоктистов А.Г, Корсуков А.С., Сидоров И.А. Высокопроизводительные вычислительные ресурсы Института динамики систем и теории управления со ран: текущее состояние, возможности и перспективы развития//Вычислительные технологии 2010. Т. 15. С. 69-81
  • Bogdanova V.G., Bychkov I.V., Korsukov A.S., Oparin G.A., Feoktistov A.G. Multiagent Approach to Controlling Distributed Computing in a Cluster Grid System//J. Comput. Syst. Sci. Int. 2014. Vol. 53. P. 713-722 DOI: 10.1134/S1064230714040030
  • Bychkov I.V., Oparin G.A., Feoktistov A.G., Bogdanova V.G., Pashinin A.A. Service-oriented multiagent control of distributed computations//Automat. Rem. Contr. 2015. Vol. 76. P. 2000-2010 DOI: 10.1134/S0005117915110090
  • Bychkov I.V., Oparin G.A., Feoktistov A.G., Sidorov I.A., Bogdanova V.G., Gorsky, S.A. Multiagent Control of Computational Systems on the Basis of Meta-monitoring and Imitational Simulation//Optoelectron., Instr. and Data Process. 2016. Vol. 52, P. 107-112 DOI: 10.3103/S8756699016020011
  • Иркутский суперкомпьютерный центр СО РАН. URL: http://hpc.icc.ru (accessed: 16.02.2017)
  • Buyya R., Broberg J., Goscinski A.M. Cloud Computing: Principles and Paradigms. Wiley, 2011. 637 p DOI: 10.1002/9780470940105
  • haran S. A Performance Comparison of Hypervisors for Cloud Computing. University of North Florida, 2012. 269 p
  • Docker. URL: http://docker.com (дата обращения: 16.02.2017).
  • QEMU. URL: http://qemu.org (дата обращения: 16.02.2017).
  • KVM. URL: http://www.linux-kvm.org (дата обращения: 16.02.2017).
  • Xen. URL: http://cam.ac.uk/research/srg/netos/projects/archive/xen (дата обращения: 16.02.2017).
  • vSphere ESXi. URL: https://vmware.com/support/vsphere-hypervisor.html (дата обращения: 16.02.2017).
  • Bumgardner V.K. OpenStack in Action. Manning Publications, 2016. 358 p.
  • Apache CloudStack. URL: https://cloudstack.apache.org/(дата обращения: 16.02.2017).
  • Euacalyptus. URL: http://www.eucalyptus.com/(дата обращения: 16.02.2017).
  • OpenNebula. URL: https://opennebula.org (дата обращения: 16.02.2017).
  • Bichkov I.V., Oparin G.A., Novopashin A.P., Sidorov I.A. Agent-Based Approach to Monitoring and Control of Distributed Computing Environment//Parallel Computing Technologies: 13th International Conference, PaCT 2015 (Petrozavodsk, Russia, August 31 -September 4 2015). LNCS, Vol. 9251. P. 253-257. 7_24 DOI: 10.1007/978-3-319-21909-
  • Sidorov I.A. Methods and Tools to Increase Fault Tolerance of High-performance Computing Systems//In proc. of the 39th International Convention on information and communication technology, electronics and microelectronics, MIPRO-2016 (Opatija, Croatia, 30 May-3 June 2016). Riejka: CSICTEM 2016. P. 242-246 DOI: 10.1109/MIPRO.2016.7522142
  • Feoktistov A.G, Sidorov I.A. Logical-Probabilistic Analysis of Distributed Computing//In proc. of the 39th International Convention on information and communication technology, electronics and microelectronics, MIPRO-2016 (Opatija, Croatia, May 30 -June 3 2016). Riejka: CSICTEM 2016. P. 247-252 DOI: 10.1109/MIPRO.2016.7522142
  • Hastie T., Tibshirani R., Friedman J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2001, 533 p
  • Шоломов Л.А. Логические методы исследования дискретных моделей выбора. М.: Наука, 1989. 288 с.
  • GPSS World Tutorial Manual. URL: http://www.minutemansoftware.com (дата обращения: 16.02.2017).
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