Chromium: a stream-processing framework for interactive rendering on clusters
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Virtualizing I/O Devices on VMware Workstation's Hosted Virtual Machine Monitor
Proceedings of the General Track: 2002 USENIX Annual Technical Conference
A comparison of software and hardware techniques for x86 virtualization
Proceedings of the 12th international conference on Architectural support for programming languages and operating systems
VMM-independent graphics acceleration
Proceedings of the 3rd international conference on Virtual execution environments
ACM SIGGRAPH 2007 courses
Larrabee: a many-core x86 architecture for visual computing
ACM SIGGRAPH 2008 papers
Secure 3D graphics for virtual machines
Proceedings of the Second European Workshop on System Security
LiteGreen: saving energy in networked desktops using virtualization
USENIXATC'10 Proceedings of the 2010 USENIX conference on USENIX annual technical conference
SHARC: A scalable 3D graphics virtual appliance delivery framework in cloud
Journal of Network and Computer Applications
The best of both worlds with on-demand virtualization
HotOS'13 Proceedings of the 13th USENIX conference on Hot topics in operating systems
Pegasus: coordinated scheduling for virtualized accelerator-based systems
USENIXATC'11 Proceedings of the 2011 USENIX conference on USENIX annual technical conference
Providing safe, user space access to fast, solid state disks
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
Operating system support for augmented reality applications
HotOS'13 Proceedings of the 14th USENIX conference on Hot Topics in Operating Systems
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Modern graphics co-processors (GPUs) can produce high fidelity images several orders of magnitude faster than general purpose CPUs, and this performance expectation is rapidly becoming ubiquitous in personal computers. Despite this, GPU virtualization is a nascent field of research. This paper introduces a taxonomy of strategies for GPU virtualization and describes in detail the specific GPU virtualization architecture developed for VMware's hosted products (VMware Workstation and VMware Fusion). We analyze the performance of our GPU virtualization with a combination of applications and micro bench-marks. We also compare against software rendering, the GPU virtualization in Parallels Desktop 3.0, and the native GPU. We find that taking advantage of hardware acceleration significantly closes the gap between pure emulation and native, but that different implementations and host graphics stacks show distinct variation. The micro bench-marks show that our architecture amplifies the overheads in the traditional graphics API bottlenecks: draw calls, downloading buffers, and batch sizes. Our virtual GPU architecture runs modern graphics-intensive games and applications at interactive frame rates while preserving virtual machine portability. The applications we tested achieve from 86% to 12% of native rates and 43 to 18 frames per second with VMware Fusion 2.0.