skip to main content
research-article

Exploiting I/O Reordering and I/O Interleaving to Improve Application Launch Performance

Published:25 February 2017Publication History
Skip Abstract Section

Abstract

Application prefetchers improve application launch performance through either I/O reordering or I/O interleaving. However, there has been no proposal to combine the two techniques together, missing the opportunity for further optimization. We present a new application prefetching technique to take advantage of both the approaches. We evaluated our method with a set of applications to demonstrate that it reduces cold start application launch time by 50%, which is an improvement of 22% from the I/O reordering technique.

References

  1. Sedat Akyürek and Kenneth Salem. 1995. Adaptive block rearrangement. ACM Trans. Comput. Syst. 13, 2 (1995), 89--121. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Medha Bhadkamkar, Jorge Guerra, Luis Useche, Sam Burnett, Jason Liptak, Raju Rangaswami, and Vagelis Hristidis. 2009. BORG: Block-reORGanization for self-optimizing storage systems. In Proceedings of the USENIX Conference on File and Storage Technologies (FAST’09). 183--196. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Blktrace(8). 2006. Linux Man Page. Retrieved from http://linux.die.net/man/8/blktrace.Google ScholarGoogle Scholar
  4. John S. Bucy and Gregory R. Ganger. 2003. The DiskSim Simulation Environment Version 3.0 Reference Manual. Technical Report CMU--CS--03--102. Department of Computer Science, Carnegie-Mellon University.Google ScholarGoogle Scholar
  5. Xiaoning Ding, Song Jiang, Feng Chen, Kei Davis, and Xiaodong Zhang. 2007. DiskSeen: Exploiting disk layout and access history to enhance I/O prefetch. In Proceedings of the USENIX Annual Technical Conference (USENIX ATC’07). 261--274. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Hai Huang, Wanda Hung, and Kang G. Shin. 2005. FS2: Dynamic data replication in free disk space for improving disk performance and energy consumption. In Proceedings of the ACM Symposium on Operating Systems Principles (SOSP’05). 263--276. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Yongsoo Joo, Junhee Ryu, Sangsoo Park, and Kang G. Shin. 2011. FAST: Quick application launch on solid-state drives. In Proceedings of the USENIX Conference on File and Storage Technologies (FAST’11). 259--272. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Zhenmin Li, Zhifeng Chen, Sudarshan M. Srinivasan, and Yuanyuan Zhou. 2004. C-Miner: Mining block correlations in storage systems. In Proceedings of the USENIX Conference on File and Storage Technologies (FAST’04). 173--186. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Ketil Lund and Vera Goebel. 2003. Adaptive disk scheduling in a multimedia DBMS. In Proceedings of the 11th ACM International Conference on Multimedia (MULTIMEDIA’03). 65--74. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Anna Povzner, Tim Kaldewey, Scott Brandt, Richard Golding, Theodore M. Wong, and Carlos Maltzahn. 2008. Efficient guaranteed disk request scheduling with fahrrad. In Proceedings of the 3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008 (EUROSYS’08). 13--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. A. L. N. Reddy, Jim Wyllie, and K. B. R. Wijayaratne. 2005. Disk scheduling in a multimedia I/O system. ACM Trans. Multimedia Comput. Commun. Appl. 1, 1 (Feb. 2005), 37--59. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Mark E. Russinovich and David Solomon. 2004. Microsoft Windows Internals (4th ed.). Microsoft Press, 458--462.Google ScholarGoogle Scholar
  13. Jiri Schindler, Sandip Shete, and Keith A. Smith. 2011. Improving throughput for small disk requests with proximal I/O. In Proceedings of the USENIX Conference on File and Storage Technologies (FAST’11). 133--147. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Bruce L. Worthington, Gregory R. Ganger, and Yale N. Patt. 1994. Scheduling algorithms for modern disk drives. In Proceedings of the ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems (SIGMETRICS’94). 241--251. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Xuechen Zhang, Kei Davis, and Song Jiang. 2011. QoS support for end users of I/O-intensive applications using shared storage systems. In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC’11). Article 18, 12 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Exploiting I/O Reordering and I/O Interleaving to Improve Application Launch Performance

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on Storage
        ACM Transactions on Storage  Volume 13, Issue 1
        Special Issue on USENIX FAST 2016 and Regular Papers
        February 2017
        201 pages
        ISSN:1553-3077
        EISSN:1553-3093
        DOI:10.1145/3054178
        • Editor:
        • Sam H. Noh
        Issue’s Table of Contents

        Copyright © 2017 ACM

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 25 February 2017
        • Accepted: 1 November 2016
        • Revised: 1 October 2016
        • Received: 1 March 2016
        Published in tos Volume 13, Issue 1

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader
      About Cookies On This Site

      We use cookies to ensure that we give you the best experience on our website.

      Learn more

      Got it!