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Implementation of GPU virtualization using PCI pass-through mechanism

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Abstract

As a general purpose scalable parallel programming model for coding highly parallel applications, CUDA from NVIDIA provides several key abstractions: a hierarchy of thread blocks, shared memory, and barrier synchronization. It has proven to be rather effective at programming multithreaded many-core GPUs that scale transparently to hundreds of cores; as a result, scientists all over the industry and academia are using CUDA to dramatically expedite on production and codes. GPU-based clusters are likely to play an essential role in future cloud computing centers, because some computation-intensive applications may require GPUs as well as CPUs. In this paper, we adopted the PCI pass-through technology and set up virtual machines in a virtual environment; thus, we were able to use the NVIDIA graphics card and the CUDA high performance computing as well. In this way, the virtual machine has not only the virtual CPU but also the real GPU for computing. The performance of the virtual machine is predicted to increase dramatically. This paper measured the difference of performance between physical and virtual machines using CUDA, and investigated how virtual machines would verify CPU numbers under the influence of CUDA performance. At length, we compared CUDA performance of two open source virtualization hypervisor environments, with or without using PCI pass-through. Through experimental results, we will be able to tell which environment is most efficient in a virtual environment with CUDA.

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Acknowledgement

This work was supported in part by the National Science Council, Taiwan, ROC, under grant numbers NSC 102-2218-E-029-002, NSC 101-2218-E-029-004, and NSC 102-2622-E-029-005-CC3. This work also supported in part by Tunghai University, Taiwan ROC, under grant number GREEnS 04-2.

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Authors and Affiliations

  1. Department of Computer Science, Tunghai University, Taichung, 40704, Taiwan

    Chao-Tung Yang, Jung-Chun Liu & Hsien-Yi Wang

  2. Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan

    Ching-Hsien Hsu

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  1. Chao-Tung Yang
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  2. Jung-Chun Liu
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Correspondence to Chao-Tung Yang.

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Yang, CT., Liu, JC., Wang, HY. et al. Implementation of GPU virtualization using PCI pass-through mechanism. J Supercomput 68, 183–213 (2014). https://doi.org/10.1007/s11227-013-1034-4

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