Research and application of GPU pass-through based on KVM in desktop cloud

DOI

10.2991/mecs-17.2017.73How to use a DOI?

Keywords

Openstack Cloud;KVM ;Vfio-pci;GPU Passthrough with qemu

Abstract

At present,the desktop cloud has come into people's life.You'll see them in some companies, offices, and school labs.The problem I am trying to solve in this paper is that because the computing power of virtual desktop is provided by the virtual machine,and then transmit data to the virtual desktop to display through the network,so compared with the traditional PC in terms of performance, there are still gaps, it is difficult to cope with the application of high load ,such as 3D animation, high-definition video processing, etc.The approach I adopt to solve the problem is that we can use vfio-pci technology to direct GPU to a virtual machine,Enables the virtual machine to monopolize the graphics card,And be able to achieve more than 90% of the performance of graphics,This is a huge improvement for users, and many desktop cloud users are not limited to general enterprise applications,Such as Office, Web applications, Flash playback, video playback and so on.After pass-through,Users can carry out high load applications, 3D animation, high-definition video processing, etc.There are several companies doing virtualization, but KVM is an open source virtualization solution, its market share is not very high, KVM virtualization based on direct display card is not a mature scheme, this is another contribution to the open source.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lin Zhou
AU  - Jianxin Song
AU  - Jinkun Yuan
AU  - Haifeng Han
PY  - 2016/06
DA  - 2016/06
TI  - Research and application of GPU pass-through based on KVM in desktop cloud
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.73
DO  - 10.2991/mecs-17.2017.73
ID  - Zhou2016/06
ER  -