Providing CUDA Acceleration to KVM Virtual Machines in InfiniBand Clusters with rCUDA

Ferran Perez, Carlos Reaño, Federico Silla

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

11 Citations (Scopus)
202 Downloads (Pure)

Abstract

There is a trend towards using graphics processing units (GPUs) not only for graphics visualization, but also for accelerating scientific applications. But their use for this purpose is not without disadvantages: GPUs increase costs and energy consumption. Furthermore, GPUs are generally underutilized. Using virtual machines could be a possible solution to address these problems, however, current solutions for providing GPU acceleration to virtual machines environments, such as KVM or Xen, present some issues. In this paper we propose the use of remote GPUs to accelerate scientific applications running inside KVM virtual machines. Our analysis shows that this approach could be a possible solution, with low overhead when used over InfiniBand networks.
Original languageEnglish
Title of host publicationDistributed Applications and Interoperable Systems
Subtitle of host publication16th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS)
PublisherSpringer
Pages82-95
ISBN (Electronic)978-3-319-39577-7
ISBN (Print)978-3-319-39576-0
DOIs
Publication statusPublished - 24 May 2016
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume 9687
ISSN (Print)0302-9743

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  • Cite this

    Perez, F., Reaño, C., & Silla, F. (2016). Providing CUDA Acceleration to KVM Virtual Machines in InfiniBand Clusters with rCUDA. In Distributed Applications and Interoperable Systems : 16th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS) (pp. 82-95). (Lecture Notes in Computer Science; Vol. 9687). Springer. https://doi.org/10.1007/978-3-319-39577-7_7