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Volume 42 Issue 11
Nov.  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(11): 2340-2348.
YANG Jingwei, MA Kai, LONG Xianget al. Virtualized GPU computing platform in clustered system environment[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(11): 2340-2348. doi: 10.13700/j.bh.1001-5965.2015.0731(in Chinese)
Citation: YANG Jingwei, MA Kai, LONG Xianget al. Virtualized GPU computing platform in clustered system environment[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(11): 2340-2348. doi: 10.13700/j.bh.1001-5965.2015.0731(in Chinese)
shu

Virtualized GPU computing platform in clustered system environment

doi: 10.13700/j.bh.1001-5965.2015.0731

  • School of Computer Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

  • Received Date: 09 Nov 2015
  • Rev Recd Date: 15 Jan 2016
  • Publish Date: 20 Nov 2016
    Abstract
  • A virtualized GPU computing platform is proposed for clustered systems, which are often equipped with GPUs in some nodes. All GPUs in system are uniformly abstracted as virtualized ones in a commonly accessed resource pool. Legacy GPU programs can execute on the virtualized GPU computing platform without any modification and any free virtualized GPU in the common resource pool is available to it, which relieves the burden of MPI programming. The platform frees programs with the limit of GPUs in local node and makes it possible for them to access any available GPU in distributed nodes, leading to higher system utilization and throughput. Based on pipelined communication, the run-time overhead and inter-node transmitting latency in virtualized GPU computing platform are hidden by intra-node memory copying and GPU computing. Compared with the non-pipelined communication, the total transmission latency is decreased by approximately 50%-70%. It results in a comparable performance with intra-node local data transmission.

     

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