Delegating OpenGL commands to host for hardware support in virtualized environments

Younghyun Joo, Dongwoo Lee, Young Ik Eom

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

Today, the virtualization is a very important technology which is widely used in various area, from small mobile devices to virtual machine (VM) servers for large scale cloud computing. Now, hypervisor provides CPU and memory resources for the VMs with high performance like native machine through many researches on the virtualized environment. However, device virtualization techniques, especially those for GPU devices, are less studied than the other virtualization techniques. It is a chief obstacle to perform graphics processing in the virtualized environment. Since VM cannot access the physical GPU device directly, existing GPU device virtualization techniques have some limitations on 3D acceleration. Especially, those techniques spend more time to perform graphics processing because they use software rendering on the Mesa Software Fallback module in the guest OS. In this paper, we propose a GPU device virtualization technique that can improve OpenGL graphics performance. By using concurrent I/O request queue between the host emulation process and the guest OS, GPU device can be accessed directly. Our scheme can avoid graphics processing in the graphics stack of the guest OS and also can reduce vmexit overheads. The emulation process can perform the graphics processing using GPU hardware rendering. Our evaluation shows that the proposed technique has about 2.5× higher frame rate than existing Mesa software rendering.

Original languageEnglish
DOIs
StatePublished - 2014
Event8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014 - Siem Reap, Cambodia
Duration: 9 Jan 201411 Jan 2014

Conference

Conference8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014
Country/TerritoryCambodia
CitySiem Reap
Period9/01/1411/01/14

Keywords

  • Acceleration
  • Device virtualization
  • GPU
  • OpenGL
  • Virtualization

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