Skip to main content
SpringerLink
Log in

Performance issues and performance analysis tools for HPC cloud applications: a survey

  • Published:
Computing Aims and scope Submit manuscript

Abstract

Cloud Computing is an eminent emerging technology that surpasses Grids from their IT resource administrations and arduous Grid middleware solutions. At present, users could access an abundant number of pre-defined cloud services or run their programs on demand as a pay-as-you-go processing model without much distribution problems. In addition, the IT business market has pumped enough revenue for establishing salient common-use cloud solutions. Despite adequate researchers have been involved in the cloud development, scientific application developers are still reluctant to execute their applications in the cloud due to the performance concerns, such as, scalability, availability, and service level agreement violations of the cloud providers. In this paper, a survey of various High Performance Computing (HPC) applications and possible performance concerns while executing applications in cloud is presented. Pointing out the need for Performance Analysis (PA) tools, this paper focuses on the study of cloud-based PA tools in detail. This paper could leverage HPC application developers to cope with the performance issues and to best utilize the available performance analysis tools of clouds.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Alexandru I, Simon O, Nezih YM, Radu P, Thomas F, Epema Dick HJ (2011) Performance analysis of cloud computing services for many-tasks scientific computing. IEEE Trans Parallel Distributed Comput 22(6):931–944

    Article  Google Scholar 

  2. Amazon’s Cloud (2011). http://www.itnews.com.au/News/153451,stress-tests-rain-on-amazons-cloud.aspx. Accessed 31 Aug 2012

  3. Amazon Cloud Watch. http://aws.amazon.com/cloudwatch/. Accessed 31 Aug 2012

  4. Ang L, Xiaowei Y, Ming Z (2011) Comparing public-cloud providers. IEEE Internet Comput 15(2): 50–53

    Google Scholar 

  5. Anton B, Rajkumar B, Young CL, Albert Z (2012) A taxonomy and survey of energy-efficient data centers and cloud computing systems. Technical, Report, CLOUDS-TR-2010-3. arXiv:1007.0066v2

  6. Arto O, Pasi T (2011) Developing a cloud business models: a case study on cloud gaming. IEEE Softw/IEEE Comput Soc 28(4):42–47

    Google Scholar 

  7. Ashino Y, Nakae M (2012) Virtual machine migration method between different hypervisor implementations and its evaluation. In: Proceedings of International Conference on AINA, pp 1089–1094

  8. Balaji P, Buntinas D, Goodell D, Gropp W, Hoefler T, Kumar S, Lusk E, Thakur R, Traeff JL (2011) MPI on millions of cores. Parallel Process Lett (PPL) 21(1):45–60

    Article  Google Scholar 

  9. Birkenheuer G, Brinkmann A, Kaiser J, Keller A, Keller M, Kleineweber C, Konersmann C, Nieho\(\ddot{\rm r}\) ster O, Scha\(\ddot{\rm f}\)er T, Simon J, Wilhelm M (2012) Virtualized HPC: a contradiction in terms? Softw Pract Exper 42: 485–500

    Google Scholar 

  10. Borenstein N, Blake J (2011) Cloud computing standards: where’s the beef? Internet Comput IEEE 15(3):74–78

    Article  Google Scholar 

  11. Bungo J (2011) Embedded systems programming in the cloud: a novel approach for academia. IEEE Potentials 30(1):17–23

    Article  Google Scholar 

  12. Lewis N (2011) AT and T, Accenture service stores medical images in cloud. http://www.informationweek.com/healthcare/interoperability/att-accenture-service-stores-medical-ima/232200581. Accessed 31 Aug 2012

  13. CloudKick Tool. https://www.cloudkick.com/. Accessed 31 Aug 2012

  14. CloudStatus Tool. http://www.download.hyperic.com/pdf/cloudstatus.pdf. Accessed 31 Aug 2012

  15. Díaz-Sánchez Dl, Almenarez F, Marín A, Proserpio D, Cabarcos PA (2011) Media cloud: an open cloud computing middleware for content management. IEEE Trans Consumer Electron 57(2):970–978

    Article  Google Scholar 

  16. De Chaves SA, Uriarte RB, Westphall CB (2011) Toward an architecture for monitoring private clouds. IEEE Commun Magazine 49(12):130–137

    Article  Google Scholar 

  17. Ganglia Tool. http://www.ganglia.info/. Accessed 31 Aug 2012

  18. Grobauer B, Walloschek T, Stocker E (2011) Understanding cloud computing vulnerabilities. Secur Privacy IEEE 9(2):50–57

    Article  Google Scholar 

  19. Gupta A, Milojicic D (2012) Evaluation of HPC applications on cloud. Technical Reports, HP laboratories. http://www.hpl.hp.com/techreports/2011/HPL-2011-132.html. Accessed 31 Aug 2012

  20. Hong-Ling T, Schahram D (2010) Cloud computing for small research groups in computational science and engineering: current status and outlook. Computing 91(1):75–91. doi:10.1007/s00607-010-0120-1

    Google Scholar 

  21. Hossfeld T, Schatz R, Varela M, Timmerer C (2012) Challenges of QoE management for cloud applications. IEEE Commun Magazine 50:28–36

    Google Scholar 

  22. Ian F, Yong Z, Ioan R, Shiyong L (2008) Cloud computing and grid computing 360-degree compared. In: Proceedings of Grid Computing Environments Workshop, GCE ’08, doi:10.1109/GCE.2008.4738445, pp 1–10

  23. Information Manager Tool. http://opennebula.org/documentation:archives:rel2.0:img. Accessed 31 Aug 2012

  24. InterMapper Tool. http://www.intermapper.com/about-us/news-details.aspx?newsid=26. Accessed 31 Aug 2012

  25. Brandic I, Dustdar S (2011) Grid vs cloud: a technology comparison. Informat Technol 53(4):173–179. doi:10.1524/itit.2011.0640

    Article  Google Scholar 

  26. Vöckler J-S, Juve G, Deelman E, Rynge M, Berriman B (2011) Experiences using cloud computing for a scientific workflow application. In: Proceedings of the 2nd international workshop on Scientific cloud, computing, ScienceCloud11. doi:10.1145/1996109.1996114

  27. Juve G, Deelman E (2010) Scientific workflows and clouds. ACM Crossroads 16(1):14–18

    Article  Google Scholar 

  28. Kumar K, Yung-Hsiang Lu (2010) Cloud computing for mobile users: can offloading computation save energy? Computer 43(4):51–56

    Article  Google Scholar 

  29. Ye K, Che J, He Q, Huang D, Jiang X (2012) Performance combinative evaluation from single virtual machine to multiple virtual machine systems. Int J Numer Anal Model 9(2):351–370

    Google Scholar 

  30. Kishor K, Donghoon K, Torsten H, Frank M (2012) Assessing HPC failure detectors for MPI jobs. Accepted at 20th Euromicro International Conference on Parallel. Distributed and Network-Based Computing, Munich, Germany

  31. Knight D, Shams K, Chang G, Soderstrom T (2012) Evaluating the Efficacy of the Cloud for Cluster Computation. In: Proceedings of IEEE Aerospace Conference, pp 1–10

  32. LogicMonitor Tool. http://www.logicmonitor.com/quick-tour/hosted-monitoring-architecture/. Accessed 31 Aug 2012

  33. Luis M, Vaquero Luis Rodero-Merino, Morán Daniel (2010) Locking the sky: a survey on IaaS cloud security. Computing 91(1):93–118. doi:10.1007/s00607-010-0140-x

    Google Scholar 

  34. Bull M, Hill J, Simpson A (2009) A survey of HPC systems and applications in Europe. www.prace-project.eu/IMG/pdf/Bull_DEISAPRACE.pdf. Accessed 31 Aug 2012

  35. Mell P, Grance T. The NIST definition of cloud computing. http://www.nist.gov/itl/cloud/upload/cloud-def-v15.pdf. Accessed 31 Aug 2012

  36. Microsoft Cloud Outages. http://www.rscsolutions.com/news/post/microsoft-explains-recent-cloud-outage. Accessed 31 Aug 2012

  37. Nagios Tool. http://www.nagios.org/. Accessed 31 Aug 2012

  38. Narasimhan B, Nichols R (2011) State of cloud applications and platforms: the cloud adopters’ view. Computer 44(3):24–28

    Article  Google Scholar 

  39. Nikolaev R, Back G (2011) Perfctr-Xen: a framework for performance counter virtualization. Proc 7th ACM SIGPLAN/SIGOPS Int Conf Virtual Execut Environ 46(7):15–26

  40. Nimsoft Tool. http://www.nimsoft.com/solutions/nimsoft-monitor/cloud.html. Accessed 31 Aug 2012

  41. Oliker L, Canning A, Carter J, Shalf J, Ethier S (2004) Scientific computations on modern parallel vector systems. In: Proceedings of SC04 International Conference for High Performance Computing, Networking, Storage, and Analysis, Pittsburgh, pp 6–12

  42. Ranabahu A, Anderson P, Sheth A (2011) The cloud agnostic e-science analysis platform. IEEE Internet Comput 15(6):85–89

    Article  Google Scholar 

  43. Rehr JJ, Vila FD, Gardner JP, Svec L, Prange M (2010) Scientific computing in the cloud. Comput Sci Eng 12(3):34–43

    Article  Google Scholar 

  44. Schaffer HE (2009) X as a service, cloud computing, and the need for good judgment. IT Professional 11(5):4–5

    Article  Google Scholar 

  45. Shajulin B. HPCCLoud Research Laboratory for Tool Development. http://www.sxcce.edu.in/hpccloud. Accessed 31 Aug 2012

  46. Sakr Sherif, Liu Anna, Batista Daniel M, Alomari Mohammad (2011) A survey of large scale data management approaches in cloud environments. IEEE Commun Surv Tutor 13(3):311–335

    Article  Google Scholar 

  47. Ortiz S Jr (2011) The problem with cloud-computing standardization. IEEE Computer 44(7):13–16

    Google Scholar 

  48. Sobie RJ, Agarwal A, Anderson M, Armstrong P, Fransham K, Gable I, Harris D, Leavett-Brown C, Paterson M, Penfold-Brown D, Vliet M, Charbonneau A, Impey R, Podaima W (2011) Data intensive high energy physics analysis in a distributed cloud. http://arxiv.org/abs/1101.0357. Accessed 31 Aug 2012

  49. Verena K, Debabrata D, Gre gory F, Sofia K, Anastasia A (2011) Optimal service pricing for a cloud cache. IEEE Trans Knowledge Data Eng 23(9):1345–1358

    Google Scholar 

  50. Windows Azure Tool. http://archive.msdn.microsoft.com/wazdmon. Accessed 31 Aug 2012

Download references

Acknowledgments

This research work is supported in part by the financial support provided by the Returning Experts programme of CIMOnline. The author appreciates the many discussions with and critical insights provided by Prof. Dr. Michael Gerndt of Technische Universitat Muenchen during his PostDoc tenure in TUM, Germany. In addition, the author thanks Shri. S. Sudershan Rao, Scientist of the Department of Science and Technology, India, and the reviewers of this survey paper for nourishing this work.

Author information

Authors and Affiliations

  1. HPCCLoud Reserach Laboratory, St.Xavier’s Catholic College of Engineering, Anna University, Nagercoil, 629003, India

    Shajulin Benedict

Authors
  1. Shajulin Benedict
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shajulin Benedict.

Additional information

This work is partially funded by the HPCCLoud project, an ongoing research grant, under Returning-Experts programme of CIMOnline, GIZ, Germany, and Department of Science and Technology, India.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Benedict, S. Performance issues and performance analysis tools for HPC cloud applications: a survey. Computing 95, 89–108 (2013). https://doi.org/10.1007/s00607-012-0213-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00607-012-0213-0

Keywords

Mathematics Subject Classification

Search

Navigation