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ABSTRACT
As networks get faster, it becomes more feasible to render large data sets remotely. For example, it is useful to run large scientific simulations on remote compute servers but visualize the results of those simulations on one or more local displays. The WireGL project at Stanford is researching new techniques for rendering over a network. For many applications, we can render remotely over a gigabit network to a tiled display with little or no performance loss over running locally. One of the elements of WireGL that makes this performance possible is our ability to track the graphics state of a running application.
In this paper, we will describe our techniques for tracking state, as well as efficient algorithms for computing the difference between two graphics contexts. This fast differencing operation allows WireGL to transmit less state data over the network by updating server state lazily. It also allows our system to context switch between multiple graphics applications several million times per second without flushing the hardware accelerator. This results in substantial performance gains when sharing a remote display between multiple clients.
network to a tiled display with little or no performance loss over running locally. One of the elements of WireGL that makes this performance possible is our ability to track the graphics state of a running application.
In this paper, we will describe our techniques for tracking state, as well as efficient algorithms for computing thi
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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OpenGL specifications. http://www.opengl.org/Documentation/Specs.html .
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Personal correspondence with Nick Triantos, NVIDIA Corporation.
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The OpenGL Utility Toolkit. http://reality.sgi.com/mjk/#glut .
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CITED BY 19
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Greg Humphreys , Ian Buck , Matthew Eldridge , Pat Hanrahan, Distributed rendering for scalable displays, Proceedings of the 2000 ACM/IEEE conference on Supercomputing (CDROM), p.30-es, November 04-10, 2000, Dallas, Texas, United States
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Greg Humphreys , Mike Houston , Ren Ng , Randall Frank , Sean Ahern , Peter D. Kirchner , James T. Klosowski, Chromium: a stream-processing framework for interactive rendering on clusters, ACM Transactions on Graphics (TOG), v.21 n.3, July 2002
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R. Stevens , M. E. Papka , M. Kilgard , G. Humphreys , T. Funkhouser, Commodity graphics accelerators for scientific visualization, Proceedings of the conference on Visualization '01, October 21-26, 2001, San Diego, California
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H. Andres Lagar-Cavilla , Niraj Tolia , M. Satyanarayanan , Eyal de Lara, VMM-independent graphics acceleration, Proceedings of the 3rd international conference on Virtual execution environments, June 13-15, 2007, San Diego, California, USA
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Greg Humphreys , Mike Houston , Ren Ng , Randall Frank , Sean Ahern , Peter D. Kirchner , James T. Klosowski, Chromium: a stream-processing framework for interactive rendering on clusters, ACM SIGGRAPH ASIA 2008 courses, p.1-10, December 10-13, 2008, Singapore
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H. Andrés Lagar-Cavilla , Niraj Tolia , Eyal de Lara , M. Satyanarayanan , David O'Hallaron, Interactive resource-intensive applications made easy, Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware, November 26-30, 2007, Newport Beach, California
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