• DocumentCode
    167421
  • Title

    Evaluating GPU Passthrough in Xen for High Performance Cloud Computing

  • Author

    Younge, Andrew J. ; Walters, John Paul ; Crago, Stephen ; Fox, Geoffrey C.

  • Author_Institution
    Pervasive Technol. Inst., Indiana Univ., Bloomington, IN, USA
  • fYear
    2014
  • fDate
    19-23 May 2014
  • Firstpage
    852
  • Lastpage
    859
  • Abstract
    With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their technical computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities clouds provide, as well as many novel computing paradigms available for data-intensive applications. However, there is concern about a performance gap that exists between the performance of IaaS when compared to typical high performance computing (HPC) resources, which could limit the applicability of IaaS for many potential scientific users. Most recently, general-purpose graphics processing units (GPGPUs or GPUs) have become commonplace within high performance computing. We look to bridge the gap between supercomputing and clouds by providing GPU-enabled virtual machines (VMs) and investigating their feasibility for advanced scientific computation. Specifically, the Xen hypervisor is utilized to leverage specialized hardware-assisted I/O virtualization and PCI passthrough in order to provide advanced HPC-centric Nvidia GPUs directly in guest VMs. This methodology is evaluated by measuring the performance of two Nvidia Tesla GPUs within Xen VMs and comparing to bare-metal hardware. Results show PCI passthrough of GPUs within virtual machines is a viable use case for many scientific computing workflows, and could help support high performance cloud infrastructure in the near future.
  • Keywords
    cloud computing; graphics processing units; natural sciences computing; parallel processing; virtual machines; virtualisation; GPGPUs; GPU passthrough evaluation; GPU-enabled virtual machines; HPC resources; HPC-centric Nvidia GPUs; IaaS; Nvidia Tesla GPUs; PCI passthrough; Xen VMs; Xen hypervisor; data-intensive applications; general-purpose graphics processing units; hardware-assisted I/O virtualization; high performance cloud computing; high performance cloud infrastructure; high performance computing; infrastructure-as-a-service; performance measurement; scientific computation; scientific computing community; scientific computing workflows; supercomputing; technical computing needs; Benchmark testing; Cloud computing; Graphics processing units; Hardware; Performance evaluation; Virtual machine monitors; Virtualization; Cloud computing; GPUs; HPC; IaaS; Scientific Computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International
  • Conference_Location
    Phoenix, AZ
  • Print_ISBN
    978-1-4799-4117-9
  • Type

    conf

  • DOI
    10.1109/IPDPSW.2014.97
  • Filename
    6969471