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Tytuł artykułu

Measure of adequacy for the supercomputer job management system model

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Konferencja
Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
Języki publikacji
EN
Abstrakty
EN
In this paper we investigate the problem of modelling modern supercomputer job management systems (JMS). When modelling the JMS, one of the main issues is the adequacy of the model used in experimental studies. The paper attempts to determine the measure of the JMS model adequacy by comparing the characteristics of two job streams, one of which was acquired from a real supercomputer and the other is obtained from the JMS model. We show that the normalized Euclidean distance between vectors of jobs residence times obtained from the job streams of the real system and the JMS model can serve as a measure of the adequacy of the JMS model. The paper also defines the reference value of the measure of adequacy corresponding to the JMS model with virtual nodes.
Rocznik
Tom
Strony
423--426
Opis fizyczny
Bibliogr. 16 poz., wz., tab.
Twórcy
  • Joint Supercomputer Center of the Russian Academy of Sciences, Leninskiy pr., 32a, Moscow, Russia
  • Joint Supercomputer Center of the Russian Academy of Sciences, Leninskiy pr., 32a, Moscow, Russia
  • Joint Supercomputer Center of the Russian Academy of Sciences, Leninskiy pr., 32a, Moscow, Russia
  • Joint Supercomputer Center of the Russian Academy of Sciences, Leninskiy pr., 32a, Moscow, Russia
  • Joint Supercomputer Center of the Russian Academy of Sciences, Leninskiy pr., 32a, Moscow, Russia
Bibliografia
  • 1. A. Reuther, et al., “Scalable system scheduling for HPC and big data,” in Journal of Parallel and Distributed Computing, vol. 111, 2018, pp. 76–92. https://dx.doi.org/10.1016/j.jpdc.2017.06.009
  • 2. A.B. Yoo, M.A. Jette, M. Grondona, “SLURM: Simple Linux Utility for Resource Management,” In Lecture Notes in Computer Science, vol 2862, 2003, pp. 44–60. https://dx.doi.org/10.1007/10968987_3
  • 3. R.L. Henderson, “Job scheduling under the Portable Batch System,” In Lecture Notes in Computer Science, vol 949, 1995, pp. 279-294. https://dx.doi.org/10.1007/3-540-60153-8_34
  • 4. SUPPZ. (In Russian) URL: http://suppz.jscc.ru/ (accessed: 23.04.2019).
  • 5. A.V. Baranov, D.S. Lyakhovets, “Comparison of the Quality of Job Scheduling in Workload Management Systems SLURM and SUPPZ,” in Scientific Services & Internet: All Facets of Parallelism: Proceedings of the International Supercomputing Conference, 2013, pp. 410–414 (in Russian).
  • 6. N.A. Simakov et al., “A Slurm Simulator: Implementation and Parametric Analysis,” in Lecture Notes in Computer Science, vol 10724, 2017, pp. 197-217. https://dx.doi.org/10.1007/978-3-319-72971-8_10
  • 7. I.M. Yakimov, M.V. Trusfus, V.V. Mokshin, and A.P. Kirpichnikov, “AnyLogic, ExtendSim and Simulink Overview Comparison of Structural and Simulation Modelling Systems,” In Proc. 3rd Russian-Pacific Conference on Computer Technology and Applications (RPC), Vladivostok, 2018, pp. 1-5. https://dx.doi.org/10.1109/RPC.2018.8482152
  • 8. S.W. Cox, “GPSS World: A brief preview,” in 1991 Winter Simulation Conference Proceedings., Phoenix, AZ, USA, 1991, pp. 59-61. https://dx.doi.org/10.1109/WSC.1991.185591
  • 9. S.R. Chelladurai, “Gridsim: a flexible simulator for grid integration study,” 2017. https://dx.doi.org/10.24124/2017/1375
  • 10. R.N. Calheiros, R. Ranjan, A. Beloglazov, C.A. De Rose, and R. Buyya, “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” in Softw: Pract. Exper., 2011, pp. 23-50. https://dx.doi.org/10.1002/spe.995
  • 11. W. Chen, and E. Deelman, “WorkflowSim: A toolkit for simulating scientific workflows in distributed environments,” in IEEE 8th International Conference on E-Science, Chicago, IL, 2012, pp. 1-8. https://dx.doi.org/10.1109/eScience.2012.6404430
  • 12. H. Xia, H. Dail, H. Casanova, and A.A. Chien, “The MicroGrid: using online simulation to predict application performance in diverse grid network environments,” in Proc. of the 2d Int. Workshop on Challenges of Large Applications in Distributed Environments, 2004, pp. 52-61. https://doi.org/10.1109/clade.2004.1309092
  • 13. W. Cirne, and F. Berman, “A model for moldable supercomputer jobs,” in Proc. 15th International Parallel and Distributed Processing Symposium. IPDPS 2001, San Francisco, CA, USA, 2001, p. 8. https://dx.doi.org/ 10.1109/IPDPS.2001.925004
  • 14. Standard Workload Format. URL: http://www.cs.huji.ac.il/labs/parallel/workload/swf.html (accessed 24.04.2019)
  • 15. U. Lublin, D.G. Feitelson, “The workload on parallel supercomputers: modeling the characteristics of rigid jobs,” in Journal of Parallel and Distributed Computing, vol. 63, issue 11, 2003, pp 1105-1122. https://dx.doi.org/ 10.1016/S0743-7315(03)00108-4
  • 16. B.M. Glinsky, A.S. Rodionov, M.A. Marchenko, D.I. Podkorytov, and D.V. Weins, “Agent-Oriented Approach to Simulate Exaflop Supercomputer with Application to Distributed Stochastic Simulation,” in Bulletin of the South Ural State University, Series «Mathematical Modelling, Programming & Computer Software». 2012, no 18(277), pp. 93-106 (in Russian).
Uwagi
1. Track 2: Computer Science & Systems
2. Technical Session: 10th Workshop on Scalable Computing
3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-864a6d53-008e-424d-98e3-853c77059e79
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