Technology that allows a GPU to be used by multiple virtual machines
GPU virtualization refers to technologies that allow the use of a GPU to accelerate graphics or GPGPU applications running on a virtual machine. GPU virtualization is used in various applications such as desktop virtualization,[1] cloud gaming[2] and computational science (e.g. hydrodynamics simulations).[3]
GPU virtualization implementations generally involve one or more of the following techniques: device emulation, API remoting, fixed pass-through and mediated pass-through. Each technique presents different trade-offs regarding virtual machine to GPU consolidation ratio, graphics acceleration, rendering fidelity and feature support, portability to different hardware, isolation between virtual machines, and support for suspending/resuming and live migration.[1][4][5][6]
^ abDowty, Micah; Sugerman, Jeremy (July 2009). Written at San Diego. "GPU Virtualization on VMware's Hosted I/O Architecture" (PDF). ACM SIGOPS Operating Systems Review. 43 (3). New York City: Association for Computing Machinery: 73–82. doi:10.1145/1618525.1618534. ISSN 0163-5980. S2CID 228328. Retrieved 10 September 2020.
^Hong, Hua-Jun; Fan-Chiang, Tao-Ya; Lee, Che-Rung; Chen, Kuan-Ta; Huang, Chun-Ying; Hsu, Cheng-Hsin (2014). GPU Consolidation for Cloud Games: Are We There Yet?. 13th Annual Workshop on Network and Systems Support for Games. Nagoya: Institute of Electrical and Electronics Engineers. pp. 1–6. doi:10.1109/NetGames.2014.7008969. ISBN 978-1-4799-6882-4. ISSN 2156-8138. S2CID 664129. Retrieved 14 September 2020.
^Cite error: The named reference passthrough-performance was invoked but never defined (see the help page).
^Yu, Hangchen; Rossbach, Christopher (25 June 2017). Full Virtualization for GPUs Reconsidered(PDF). ISCA-44 14th Annual Workshop on Duplicating, Deconstructing and Debunking. Toronto. Retrieved 12 September 2020.
^Tian, Kun; Dong, Yaozu; Cowperthwaite, David (June 2014). "A Full GPU Virtualization Solution with Mediated Pass-Through" (PDF). Proceedings of the 2014 USENIX Conference on USENIX Annual Technical Conference (USENIX ATC'14). USENIX Annual Technical Conference. Philadelphia: USENIX. pp. 121–132. ISBN 978-1-931971-10-2.
^Gottschlag, Mathias; Hillenbrand, Marius; Kehne, Jens; Stoess, Jan; Bellosa, Frank (November 2013). LoGV: Low-Overhead GPGPU Virtualization(PDF). 10th International Conference on High Performance Computing. Zhangjiajie: IEEE Computer Society. pp. 1721–1726. doi:10.1109/HPCC.and.EUC.2013.245. ISBN 978-0-7695-5088-6. Retrieved 16 September 2020.
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