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.
Márk Jelasity; Evangelia Kalyvianaki. 16th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (DAIS), Jun 2016, Heraklion, Crete, Greece. Lecture Notes in Computer Science, LNCS-9687, pp.82-95, 2016, Distributed Applications and Interoperable Systems. 〈10.1007/978-3-319-39577-7_7〉
https://hal.inria.fr/hal-01434802
Contributeur : Hal Ifip
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Dernière modification le : vendredi 13 avril 2018 - 19:56:04
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Ferran Pérez, Carlos Reaño, Federico Silla. Providing CUDA Acceleration to KVM Virtual Machines in InfiniBand Clusters with rCUDA. Márk Jelasity; Evangelia Kalyvianaki. 16th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (DAIS), Jun 2016, Heraklion, Crete, Greece. Lecture Notes in Computer Science, LNCS-9687, pp.82-95, 2016, Distributed Applications and Interoperable Systems. 〈10.1007/978-3-319-39577-7_7〉. 〈hal-01434802〉
