skip to main content
10.1145/2910017.2910636acmconferencesArticle/Chapter ViewAbstractPublication PagesmmsysConference Proceedingsconference-collections
demonstration

Efficient processing of videos in a multi-auditory environment using device lending of GPUs

Published:10 May 2016Publication History

ABSTRACT

In this paper, we present a demo that utilizes Device Lending via PCI Express (PCIe) in the context of a multi-auditory environment. Device Lending is a transparent, low-latency cross-machine PCIe device sharing mechanism without any the need for implementing application-specific distribution mechanisms. As workload, we use a computer-aided diagnosis system that is used to automatically find polyps and mark them for medical doctors during a colonoscopy. We choose this scenario because one of the main requirements is to perform the analysis in real-time. The demonstration consists of a setup of two computers that demonstrates how Device Lending can be used to improve performance, as well as its effect of providing the performance needed for real-time feedback. We also present a performance evaluation that shows its real-time capabilities of it.

References

  1. Dolphin Interconnect Solution PXH810 NTB Adapter, 2015.Google ScholarGoogle Scholar
  2. J. Duato, A. Pena, F. Silla, R. Mayo, and E. Quintana-Ortí. rCUDA: Reducing the number of GPU-based accelerators in high performance clusters. In Proc. of HPCS, pages 224--231, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  3. L. B. Kristiansen, J. Markussen, H. K. Stensland, M. Riegler, H. Kohmann, F. Seifert, R. Nordstrøm, C. Griwodz, and P. Halvorsen. Device lending in PCI Express Networks. In Proc. of NOSSDAV, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. NVIDIA Corporation. Developing a Linux Kernel Module using GPUDirect RDMA, 2015.Google ScholarGoogle Scholar
  5. PCI-SIG. PCI Express 3.1 Base Specification, 2010.Google ScholarGoogle Scholar
  6. K. Pogorelov, M. Riegler, P. Halvorsen, P. T. Schmidt, C. Griwodz, D. Johansen, S. L. Eskeland, and T. de Lange. GPU-accelerated real-time gastrointestinal diseases detection. In Proc. of CBMS, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. Riegler, K. Pogorelov, P. Halvorsen, T. de Lange, C. Griwodz, P. T. Schmidt, S. L. Eskeland, and D. Johansen. EIR - efficient computer aided diagnosis framework for gastrointestinal endoscopies. In Proc. of CBMI, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  8. M. Riegler, K. Pogorelov, J. Markussen, M. Lux, H. K. Stensland, T. de Lange, C. Griwodz, P. Halvorsen, D. Johansen, P. T. Schmidt, and S. L. Eskeland. Computer aided disease detection system for gastrointestinal examinations. In Proc. of MMSys, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Y. Wang, W. Tavanapong, J. Wong, J. Oh, and P. C. de Groen. Near real-time retroflexion detection in colonoscopy. IEEE BMHI, 17(1):143--152, 2013.Google ScholarGoogle Scholar
  10. Y. Wang, W. Tavanapong, J. Wong, J. H. Oh, and P. C. de Groen. Polyp-alert: Near real-time feedback during colonoscopy. CMPBM, 120(3):164--179, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Efficient processing of videos in a multi-auditory environment using device lending of GPUs

    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
    • Published in

      cover image ACM Conferences
      MMSys '16: Proceedings of the 7th International Conference on Multimedia Systems
      May 2016
      420 pages
      ISBN:9781450342971
      DOI:10.1145/2910017
      • General Chair:
      • Christian Timmerer

      Copyright © 2016 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 10 May 2016

      Check for updates

      Qualifiers

      • demonstration

      Acceptance Rates

      MMSys '16 Paper Acceptance Rate20of71submissions,28%Overall Acceptance Rate176of530submissions,33%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader