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The scheduling of task graphs in high performance computing as service clouds

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Języki publikacji
EN
Abstrakty
EN
In this paper we propose a new method of scheduling the distributed applications in cloud environment according to the High Performance Computing as a Service concept. We assume that applications, that are submitted for execution, are specified as task graphs. Our method dynamically schedules all the tasks using resource sharing by the applications. The goal of scheduling is to minimize the cost of resource hiring and the execution time of all incoming applications. Experimental results showed that our method gives significantly better utilization of computational resources than existing management methods for clouds.
Wydawca
Rocznik
Strony
193--195
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
  • Kielce University of Technology, Department of Information Systems, 7 Tysiąclecia Państwa Polskiego Ave., 25-314 Kielce, Poland
autor
  • Kielce University of Technology, Department of Information Systems, 7 Tysiąclecia Państwa Polskiego Ave., 25-314 Kielce, Poland
Bibliografia
  • [1] AbdelBaky M., Parashar M., Kim H., JordanKirk E. J., Sachdeva V., Sexton J., Jamjoom H., Shae Z.Y., Pencheva G., Tavakoli R., Wheeler M. F.: Enabling High Performance Computing as a Service. IEEE Computer, vol.45, no. 10, pp. 72-80, 2012.
  • [2] Gupta A., Faraboschi P., Gioachin F., Kale L. V., Kaufmann R., Lee B.S., March V., Milojicic D., Suen C.H.: Evaluating and Improving the Performance and Scheduling of HPC Applications in Cloud. IEEE Transactions on Cloud Computing, vol. 99, 2014.
  • [3] Shainer G., Liu T., Layton J., Mora J.: Scheduling strategies for HPC as a service (HPCaaS). Proc. IEEE International Conference on Cluster Computing and Workshops, 2009.
  • [4] Somasundaram T.S., Govindarajan K.: CLOUDRB: A framework for scheduling and managing High-Performance Computing (HPC) applications in science cloud. Future Generation Computer Systems, vol. 34, pp.47-65, 2014.
  • [5] Jamalian S., Rajaei H.: Data-Intensive HPC Tasks Scheduling with SDN to Enable HPC-as-a-Service. Proc. IEEE 8th International Conference on Cloud Computing (CLOUD), pp. 596-603, 2015.
  • [6] Huang K. C., Huanga T. C., Tsaia M. J., Chang H. Y., Tung Y.H.: Moldable job scheduling for HPC as a service with application speedup model and execution time information. Journal of Convergence, vol. 4, no. 4, 2013.
  • [7] Narayana S. S., Batrashev O., Jakovits P., Vainikko E.: Scalability of parallel scientific applications on the cloud. Scientific Programming, vol. 19, no. 2-3, pp. 91-105, 2011.
  • [8] Bąk S., Czarnecki R., Deniziak S.: Scheduling of Distributed Applications for High Performance Computing as a Service. Proc International Conference on Computational Methods in Sciences and Engineering, 2016.
  • [9] Sinnen O.: Task Scheduling for Parallel Systems. John Wiley, 2007.
  • [10] Hartmann S., Briskorn D.: A survey of variants and extensions of the resource-constrained project scheduling problem. European journal of operational research: EJOR. – Amsterdam, Elsevier, Vol. 207, 1 (16.11.), pp. 1-15, 2010.
  • [11] Kolisch R., Sprecher A.: PSPLIB - A project scheduling library. European Journal of Operational Research, Vol. 96, pp. 205-216, 1996.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-717c3e82-679c-4f6b-b414-b3e0b3dd427e
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