Performance prediction and evaluation of parallel applications in KVM, Xen, and VMware

Cheol Ho Hong, Beom Joon Kim, Young Pil Kim, Hyunchan Park, Hyuck Yoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Cloud computing platforms are considerably attractive for parallel applications that perform large-scale, computationally intensive tasks. These platforms can provide elastic computing resources to the parallel software owing to system virtualization technology. Almost every cloud service provider operates on a pay-per-use basis, and therefore, it is important to estimate the performance of parallel applications before deploying them. However, a comprehensive study that can predict the performance of parallel applications remains unexplored and is still a research topic. In this paper, we provide a theoretical performance model that can predict the performance of parallel applications in different virtual machine scheduling policies and evaluate the model in representative hypervisors including KVM, Xen, and VMware. Through this analysis and evaluation, we show that our performance prediction model is accurate and reliable.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages99-110
Number of pages12
Volume8632 LNCS
ISBN (Print)9783319098722, 9783319098722
DOIs
Publication statusPublished - 2014
Event20th International Conference on Parallel Processing, Euro-Par 2014 - Porto, Portugal
Duration: 2014 Aug 252014 Aug 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8632 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other20th International Conference on Parallel Processing, Euro-Par 2014
CountryPortugal
CityPorto
Period14/8/2514/8/29

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'Performance prediction and evaluation of parallel applications in KVM, Xen, and VMware'. Together they form a unique fingerprint.

  • Cite this

    Hong, C. H., Kim, B. J., Kim, Y. P., Park, H., & Yoo, H. (2014). Performance prediction and evaluation of parallel applications in KVM, Xen, and VMware. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8632 LNCS, pp. 99-110). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8632 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-09873-9_9