Tuning remote GPU virtualization for InfiniBand networks


In the past few years, a tendency towards using InfiniBand networks to interconnect high performance computing clusters can be observed. Thus, most of the supercomputers appearing in the TOP500 list either use Ethernet or InfiniBand interconnects. Regarding the latter, the complexity of the InfiniBand programming API (i.e., InfiniBand Verbs) makes it difficult for applications to get the maximum performance of these networks. In this paper we expose how we have tuned a remote GPU virtualization framework whose communications module is implemented using InfiniBand Verbs. The net result is a noticeable increase in the performance of this framework, significantly reducing the gap between remote and local GPUs.

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    Although the X-axis is shown in MB/s for clarity, notice that the test has been made using different transfer sizes from 1 KB to 60 MB.


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This work was funded by the Spanish MINECO and FEDER funds under Grant TIN2012-38341-C04-01. Authors are also grateful for the generous support provided by Mellanox Technologies.

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Correspondence to Carlos Reaño.

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Reaño, C., Silla, F. Tuning remote GPU virtualization for InfiniBand networks. J Supercomput 72, 4520–4545 (2016). https://doi.org/10.1007/s11227-016-1754-3

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  • HPC
  • InfiniBand
  • CUDA
  • Remote GPU virtualization
  • Networks
  • Performance
  • Tuning