research-article

Modeling virtual machine performance: challenges and approaches

Authors:

Ramesh Illikkal,

Don NewellAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 37, Issue 3

Pages 55 - 60

https://doi.org/10.1145/1710115.1710126

Published: 21 January 2010 Publication History

Abstract

Data centers are increasingly employing virtualization and consolidation as a means to support a large number of disparate applications running simultaneously on server platforms. However, server platforms are still being designed and evaluated based on performance modeling of a single highly parallel application or a set of homogenous work-loads running simultaneously. Since most future datacenters are expected to employ server virtualization, this paper takes a look at the challenges of modeling virtual machine (VM) performance on a datacenter server. Based on vConsolidate (a server virtualization benchmark) and latest multi-core servers, we show that the VM modeling challenge requires addressing three key problems: (a) modeling the contention of visible resources (cores, memory capacity, I/O devices, etc), (b) modeling the contention of invisible resources (shared microarchitecture resources, shared cache, shared memory bandwidth, etc) and (c) modeling overheads of virtual machine monitor (or hypervisor) implementation. We take a first step to addressing this problem by describing a VM performance modeling approach and performing a detailed case study based on the vConsolidate benchmark. We conclude by outlining outstanding problems for future work.

References

[1]

Amazon elastic compute cloud (ec2). http://www.amazon.com/ec2/.

[2]

Hp utility computing. http://h71028.www7.hp.com/enterprise/cache/308072-0-0-0-121.html

[3]

Intel virtualization technology specification for the ia-32 intel architecture. http://www.intel.com/technology/platformtechnology/virtualization/.

[4]

Intel xeon 5400 series. ftp://download.intel.com/products/processor/xeon/dc54kprodbrief.pdf.

[5]

Microsoft live mesh. http://www.mesh.com.

[6]

Spec. http://www.spec.org.

[7]

Specjbb2005. http://www.spec.org/jbb2005/.

[8]

Sysbench. http://sysbench.sourceforge.net/.

[9]

Twenty experts define cloud computing. http://cloudcomputing.syscon.com/read/612375 p.htm.

[10]

Vmware vmark. http://www.vmware.com/products/vmmark/results.html.

[11]

Webbench. http://cs.uccs.edu/ cs526/webbench/webbench.htm.

[12]

Xen, the xen virtual machine monitor. http://www.cl.cam.ac.uk/Research/SRG/netos/xen/architecture.html.

[13]

Paul Barham, Boris Dragovic, Keir Fraser, Steven Hand, Tim Harris, Alex Ho, Rolf Neugebauer, Ian Pratt, and Andrew Warfield. Xen and the art of virtualization. In SOSP '03: Proceedings of the nineteenth ACM symposium on Operating systems principles, pages 164--177, New York, NY, USA, 2003. ACM.

Digital Library

[14]

Dhruba Chandra, Fei Guo, Seongbeom Kim, and Yan Solihin. Predicting inter-thread cache contention on a chip multi-processor architecture. In HPCA '05: Proceedings of the 11th International Symposium on High-Performance Computer Architecture, pages 340--351, Washington, DC, USA, 2005. IEEE Computer Society.

Digital Library

[15]

Ludmila Cherkasova and Rob Gardner. Measuring cpu overhead for i/o processing in the xen virtual machine monitor. In ATEC '05: Proceedings of the annual conference on USENIX Annual Technical Conference, pages 24--24, Berkeley, CA, USA, 2005. USENIX Association.

Digital Library

[16]

R. Iyer et al. Datacenter-on-chip architectures: Tera-scale opportunities and challenges. Intel technology Journal, Aug 2007. http://www.intel.com/technology/itj/2007/v11i3/6-datacenter/1-abstract.htm.

[17]

Richard A. Hankins, Trung Diep, Murali Annavaram, Brian Hirano, Harald Eri, Hubert Nueckel, and John P. Shen. Scaling and characterizing database workloads: Bridging the gap between research and practice. In MICRO 36: Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture, page 151, Washington, DC, USA, 2003. IEEE Computer Society.

Digital Library

[18]

Ravi Iyer. Cqos: a framework for enabling qos in shared caches of cmp platforms. In ICS '04: Proceedings of the 18th annual international conference on Supercomputing, pages 257--266, New York, NY, USA, 2004. ACM.

Digital Library

[19]

Ravi Iyer, Li Zhao, Fei Guo, Ramesh Illikkal, Srihari Makineni, Don Newell, Yan Solihin, Lisa Hsu, and Steve Reinhardt. Qos policies and architecture for cache/memory in cmp platforms. In SIGMETRICS '07: Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, pages 25--36, New York, NY, USA, 2007. ACM.

Digital Library

[20]

M. Greenfield J.P. Casazza and K. Shi. Redefining server performance characterization for virtualization benchmarking. Aug 2006.

[21]

Seongbeom Kim, Dhruba Chandra, and Yan Solihin. Fair cache sharing and partitioning in a chip multiprocessor architecture. In PACT '04: Proceedings of the 13th International Conference on Parallel Architectures and Compilation Techniques, pages 111--122, Washington, DC, USA, 2004. IEEE Computer Society.

Digital Library

[22]

Parthasarathy Ranganathan and Norman Jouppi. Enterprise it trends and implications for architecture research. In HPCA '05: Proceedings of the 11th International Symposium on High-Performance Computer Architecture, pages 253--256, Washington, DC, USA, 2005. IEEE Computer Society.

Digital Library

[23]

Mendel Rosenblum and Tal Garfinkel. Virtual machine monitors: Current technology and future trends. Computer, 38(5):39{47, 2005.

Digital Library

[24]

Rich Uhlig, Gil Neiger, Dion Rodgers, Amy L. Santoni, Fernando C. M. Martins, Andrew V. Anderson, Steven M. Bennett, Alain Kagi, Felix H. Leung, and Larry Smith. Intel virtualization technology. Computer, 38(5):48--56, 2005.

Digital Library

[25]

Li Zhao, Ravi Iyer, Ramesh Illikkal, Jaideep Moses, Srihari Makineni, and Don Newell. Cachescouts: Fine-grain monitoring of shared caches in cmp platforms. In PACT '07: Proceedings of the 16th International Conference on Parallel Architecture and Compilation Techniques, pages 339--352, Washington, DC, USA, 2007. IEEE Computer Society.

Digital Library

Cited By

Sharanayya B Hiremath (2023)A Study on Virtual Machine Placement, its Parameters and ChallengesInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT2390554(247-254)Online publication date: 2-Dec-2023
https://doi.org/10.32628/CSEIT2390554
de Matos ELennon CViegas EAhvenjärvi MLyytinen HKuznetsov IOnatsu JBui A(2023)Integrating VirtIO and QEMU on seL4 for Enhanced Devices Virtualization Support2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom60117.2023.00149(1076-1085)Online publication date: 1-Nov-2023
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Published In

cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 37, Issue 3

December 2009

70 pages

ISSN:0163-5999

DOI:10.1145/1710115

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Copyright © 2010 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 January 2010

Published in SIGMETRICS Volume 37, Issue 3

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Sharanayya B Hiremath (2023)A Study on Virtual Machine Placement, its Parameters and ChallengesInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT2390554(247-254)Online publication date: 2-Dec-2023
https://doi.org/10.32628/CSEIT2390554
de Matos ELennon CViegas EAhvenjärvi MLyytinen HKuznetsov IOnatsu JBui A(2023)Integrating VirtIO and QEMU on seL4 for Enhanced Devices Virtualization Support2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom60117.2023.00149(1076-1085)Online publication date: 1-Nov-2023
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Matos EAhvenjärvi M(2022)seL4 Microkernel for Virtualization Use-Cases: Potential Directions towards a Standard VMMElectronics10.3390/electronics1124420111:24(4201)Online publication date: 16-Dec-2022
https://doi.org/10.3390/electronics11244201
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